Evaluation-computation

This is a collection of resources related with Evaluation Computation.

Contents

• Survey papers
• Papers
  • Community Detection/ Structure Balance
  • Robustness
  • Controllability/ Dominating Set
  • Influence Maximization/ Vital Node Identification
  • Transportation
  • Game Theory
  • Biological Network Research Direction
  • Recommendation System/ Link Prediction
  • SIR/SIS Propagation
  • Immunization
  • Privacy Protection
  • Network Representation
• Library

Survey papers

1. A survey on network community detection based on evolutionary computation. Cai Q , Ma L , Gong M. International Journal of Bio Inspired Computation, 2014. [paper]

2. Community detection in networks A user guide. Santo, Fortunato, Darko, & Hric. Physics Reports, 2016. [paper]

3. A Comprehensive Survey on Graph Neural Networks. Wu Z , Pan S , Chen F , et al. 2019. [paper]

4. Evolutionary Computation for Community Detection in Networks a Review. Pizzuti C. IEEE Transactions on Evolutionary Computation, 2018. [paper]

5. A Survey of Link Prediction in Complex Networks. Martínez, Víctor, Berzal F , Cubero J C. Acm Computing Surveys, 2016. [paper]

6. A Survey of Heterogeneous Information Network Analysis. Shi C , Li Y , Zhang J , et al. IEEE Transactions on Knowledge & Data Engineering, 2017. [paper]

7. Clustering and Community Detection in Directed Networks A Survey. Malliaros F D , Vazirgiannis M. Physics Reports, 2013. [paper]

Papers

Community Detection/ Structure Balance

1. A Memetic Algorithm for Community Detection in Complex Networks. Gach O , Hao J K. International Conference on Parallel Problem Solving from Nature-volume Part II, 2012. [paper]

2. Detecting community structure in complex networks using simulated annealing with -means algorithms. Liu J , Liu T. Physica A Statistical Mechanics & Its Applications, 2010. [paper]

3. A decomposition-based ant colony optimization algorithm for the multi-objective community detection. Ji P , Zhang S , Zhou Z P. Journal of Ambient Intelligence and Humanized Computing, 2019. [paper]

4. Multi-objective community detection in complex networks. Shi C , Yan Z , Cai Y , et al. Applied Soft Computing, 2012. [paper]

5. Multi-level learning based memetic algorithm for community detection. Ma, Lijia, Gong, Maoguo, Liu, Jie, Cai, Qing, Jiao, Licheng. Applied Soft Computing 19, 2014. [paper]

6. Memetic algorithm with simulated annealing strategy and tightness greedy optimization for community detection in networks. Cai-Hong Mua, Jin Xie, Yong Liu, Feng Chen, Yi Liu, Li-Cheng Jiao. Applied Soft Computing, 2015. [paper]

7. A local information based multi-objective evolutionary algorithm for community detection in complex networks. Cheng, Fan, Cui, et al. Applied Soft Computing, 2018. [paper]

8. MA-Net: A Reliable Memetic Algorithm for Community Detection by Modularity Optimization. Leila Moslemi Naeni, Regina Berretta, Pablo Moscato. Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, 2015. [paper]

9. Deep community detection based on memetic algorithm. Wang S , Gong M , Shen B , et al. IEEE Congress on Evolutionary Computation, 2015. [paper]

10. A Multiagent Evolutionary Method for Detecting Communities in Complex Networks. Ji J , Jiao L , Yang C , et al. Computational Intelligence, 2016. [paper]

11. Multiobjective approach for detecting communities in heterogeneous networks. Karimi-Majd A M , Fathian M. Computational Intelligence, 2017. [paper]

12. Email Community Detection Using Artificial Ant Colony Clustering. Yan Liu, QingXian Wang, Qiang Wang, Qing Yao,Yao Liu. Lecture Notes in Computer Science, 2007. [paper]

13. A Memetic Algorithm for Community Detection in Bipartite Networks. Xiaodong Wang, Jing Liu. International Conference on Neural Information Processing, 2017. [paper]

14. A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm. Xing L Z , Le H L , Hui Z. Cybernetics & Information Technologies, 2015. [paper]

15. Memetic Algorithm Using Node Entropy and Partition Entropy for Community Detection in Networks. Zalik, Krista, Rizman, et al. Information Sciences: An International Journal, 2018. [paper]

16. Clustering and Community Detection in Directed Networks A Survey. Malliaros F D , Vazirgiannis M. Physics Reports, 2013. [paper]

17. An ideal point based many-objective optimization for community detection of complex networks. Sahar Tahmasebi, Parham Moradi, Siamak Ghodsi, Alireza Abdollahpouri. Information Sciences，2019. [paper]

18. A memetic algorithm for computing and transforming structural balance in signed networks. Lijia Ma, Maoguo Gong, Haifeng Du, Bo Shen, Licheng Jiao. Knowledge-Based Systems, 2015. [paper]

19. Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks. Yuquan G , Xiongfei L , Yufei T , et al. Mathematical Problems in Engineering, 2017. [paper]

20. Finding community of brain networks based on artificial bee colony with uniform design. Zhang J , Zhu X , Feng J , et al. Multimedia Tools & Applications, 2019. [paper]

21. An improved multi-objective evolutionary algorithm for simultaneously detecting separated and overlapping communities. Liu C , Liu J , Jiang Z. Natural Computing, 2015. [paper]

22. A michigan memetic algorithm for solving the community detection problem in complex network. Mehdi Rezapoor Mirsaleh, Mohammad Reza Meybodi. Neurocomputing, 2016. [paper]

23. A Memetic Particle Swarm Optimization Algorithm for Community Detection in Complex Networks. Zhang C , Hei X , Yang D , et al. International Journal of Pattern Recognition & Artificial Intelligence, 2016. [paper]

24. Advanced modularity-specialized label propagation algorithm for detecting communities in networks. X. Liu , T. Murata. Physica A: Statistical Mechanics and its Applications, 2010. [paper]

25. Community detection in networks by using multiobjective evolutionary algorithm with decompositiony. Maoguo Gong, Lijia Ma, Qingfu Zhang, Licheng Jiao. Physica A: Statistical Mechanics and its Applications, 2012. [paper]

26. Community detection based on modularity and an improved genetic algorithm. Shang, Ronghua, Bai, Jing, Jiao, Licheng, Jin, Chao. Physica A: Statistical Mechanics and its Applications, 2013. [paper]

27. Fast computing global structural balance in signed networks based on memetic algorithm. Sun, Yixiang, Du, Haifeng, Gong, Maoguo, Ma, Lijia, Wang, Shanfeng. Physica A: Statistical Mechanics and its Applications, 2014. [paper]

28. Evolutionary algorithm and modularity for detecting communities in networks. Bilal S , Abdelouahab M. Physica A: Statistical Mechanics and its Applications, 2017. [paper]

29. A link clustering based memetic algorithm for overlapping community detection. Li M , Liu J. Physica A: Statistical Mechanics and its Applications, 2018. [paper]

30. Community detection in complex networks using extremal optimization. Duch J , Arenas A. Phys Rev E Stat Nonlin Soft Matter Phys, 2005. [paper]

31. Near linear time algorithm to detect community structures in large-scale networks. Raghavan U N , Albert, Réka, Kumara S. Physical Review E, 2007. [paper]

32. Iterated tabu search for identifying community structure in complex networks. Lü, Zhipeng, Huang W. Physical Review E, 2009. [paper]

33. Detecting network communities by propagating labels under constraints. Barber, Michael J, Clark, John W. Physical Review E, 2009. [paper]

34. Memetic algorithm for community detection in networks. Gong M , Fu B , Jiao L , et al. Physical Review E, 2011. [paper]

35. Clustering and Community. Mursel Tasgin, Amac Herdagdelen, Haluk Bingol. Physics Reports, 2007. [paper]

36. Temporal networks. Petter Holme, Jari Saramäki. Physics Reports, 2011. [paper]

37. Objective Community Detection Based on Memetic Algorithm. Peng W , Li P , Frederic A. Plos One, 2015. [paper]

38. GA-Net A Genetic Algorithm for Community Detection in Social Networks. Malliaros F D , Vazirgiannis M. Physics Reports, 2013. [paper]

39. A Memetic Algorithm for Community Detection in Complex Networks. Gach O , Hao J K. International Conference on Parallel Problem Solving from Nature-volume Part II, 2012. [paper]

40. The worldwide air transportation network: Anomalous centrality, community structure, and cities" global roles. Guimera R , Mossa S , Turtschi A , et al. Proceedings of the National Academy of Sciences, 2005. [paper]

41. Maps of random walks on complex networks reveal community structure. Rosvall, Martin, Bergstrom, Carl, & T. Proceedings of the National Academy of Sciences of the United States of America, 2008. [paper]

42. Combined neighborhood tabu search for community detection in complex networks. Gach, Olivier, Hao, et al. Rairo Operation Research, 2016. [paper]

43. Consensus clustering in complex networks. Lancichinetti A , Fortunato S. Scientific Reports, 2012. [paper]

44. Memetic search for overlapping topics based on a local evaluation of link communities. Frank Havemann, Jochen Gläser, Michael Heinz. Scientometrics, 2017. [paper]

45. Optimizing dynamical changes of structural balance in signed network based on memetic algorithm. Shanfeng Wang, Maoguo Gong, Haifeng Du, Lijia Ma, Qiguang Miao, Wei Du. Social Networks, 2016. [paper]

46. A comparative analysis of evolutionary and memetic algorithms for community detection from signed social networks. Li Y , Liu J , Liu C. Soft Computing, 2014. [paper]

47. MOEA/D-GLS: a multiobjective memetic algorithm using decomposition and guided local search. Alhindi Ahmad, Alhindi Abrar, Alhejali Atif, Alsheddy Abdullah, Tairan Nasser, Alhakami Hosam. Soft Computing, 2018. [paper]

48. Detecting composite communities in multiplex networks_ a multilevel memetic algorithm. Lijia Ma, Maoguo Gong, Jianan Yan, Wenfeng Liu, Shanfeng Wang. Swarm and Evolutionary Computation, 2017. [paper]

49. A Multiobjective Evolutionary Algorithm Based on Similarity for Community Detection from Signed Social Networks. Liu C , Liu J , Jiang Z. Cybernetics, IEEE Transactions on, 2014. [paper]

50. A Multiobjective Genetic Algorithm to Find Communities in Complex Networks. Pizzuti C. Evolutionary Computation, IEEE Transactions on, 2012. [paper]

51. Complex network clustering by multiobjective discrete particle swarm optimization based on decomposition. Gong, Maoguo, Cai, Qing, Chen, Xiaowei, Ma, Lijia. IEEE Transactions on Evolutionary Computation, 2014. [paper]

52. Evolutionary Computation for Community Detection in Networks_ A Review. Pizzuti C. IEEE Transactions on Evolutionary Computation, 2018. [paper]

53. An efficient multi-objective community detection algorithm in complex networks. Deng, Kun. Tehnicki vjesnik, 2015. [paper]

54. A Global Expectation–Maximization Approach Based on Memetic Algorithm for Vibration-Based Structural Damage Detection. Santos A , Santos R , Moisés Silva, et al. IEEE Transactions on Instrumentation and Measurement, 2017. [paper]

55. Network Structural Vulnerability_ A Multiobjective Attacker Perspective. Faramondi L , Oliva G , Panzieri S , et al. IEEE Transactions on Systems Man & Cybernetics Systems, 2018. [paper]

56. Reversing structural balance in signed networks. Du, Haifeng, He, Xiaochen, Wang, Jingjing, Feldman, Marcus W. Physica A: Statistical Mechanics and its Applications, 2018. [paper]

57. An information-theoretic framework for resolving community structure in complex networks. Martin Rosvall , Carl T. Bergstrom. Proceedings of the National academy of Sciences, 2007. [paper]

Robustness

1. Optimizing the Robustness of Scale-Free Networks with Simulated Annealing. Pierre Buesser, Fabio Daolio,Marco Tomassini. Lecture Notes in Computer Science, 2011. [paper]

2. Enhancing network robustness against targeted and random attacks using a memetic algorithm. Tang X , Liu J , Zhou M. EPL (Europhysics Letters), 2015. [paper]

3. Optimizing Network Attacks by Artificial Bee Colony. JLozano M , Carlos García-Martínez, Francisco J. Rodríguez, et al. Information Sciences, 2017. [paper]

4. A two-level learning strategy based memetic algorithm for enhancing community robustness of networks. Wenfeng, Liu, Maoguo, et al. Information Sciences An International Journal, 2018. [paper]

5. A memetic algorithm for enhancing the robustness of scale-free networks against malicious attacks. Jing, Liu, Mingxing, et al. Physica A Statistical Mechanics & Its Applications, 2014. [paper]

6. Tabu Search enhances network robustness under targeted attacks. Sun, Shi-wen, Ma, Yi-lin, Li, Rui-qi, Wang, Li, Xia, Cheng-yi. Physica A Statistical Mechanics & Its Applications, 2016. [paper]

7. Optimizing robustness of complex networks with heterogeneous node functions based on the Memetic Algorithm. Taocheng W , Jiajing W , Wei Y. Physica A Statistical Mechanics & Its Applications, 2018. [paper]

8. Mobility Robustness Optimization in Femtocell Networks Based on Ant Colony Algorithm. Zhang H , Liu H , Ma W , et al. Ieice Transactions on Communications, 2012. [paper]

9. Invulnerability of grown Peer-to-Peer networks under progressive targeted attacks. Peng H , Zhao D , Han J , et al. Physica A Statistical Mechanics & Its Applications, 2015. [paper]

10. Robustness and fragility in coupled oscillator networks under targeted attacks. Yuan T , Aihara K , Tanaka G. Physical Review E, 2017. [paper]

Controllability/ Dominating Set

1. On structural controllability of complex networks using polar placement. Yao, Peng, Li, Xiang. Control Conference. IEEE, 2014. [paper]

2. Study on network structural controllability based on topology decomposition. Han H , Li X , Zhao S. Control & Decision Conference. IEEE, 2015. [paper]

3. An index to measure controllability of complex networks. Zong-Yuan T , Ning C , Chen D , et al. Chinese Control Conference， 2017. [paper]

4. Robust Multiobjective Controllability of Complex Neuronal Networks. Yang Tang, Huijun Gao, Wei Du, Jianquan Lu, Athanasios V. Vasilakos, and Jurgen Kurths. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015. [paper]

5. Structural controllability of multi-agent networks importance of individual agents. Mohammad Amin Rahimian, Amir G. Aghdam . Proceedings of the American Control Conference, 2013. [paper]

6. Controllability metrics, limitations and algorithms for complex networks. Pasqualetti, Fabio, Zampieri, Sandro, Bullo, Francesco. IEEE Transactions on Control of Network Systems, 2014. [paper]

7. Identifying driver nodes in the human signaling network using structural controllability analysis. Xueming Liu, Linqiang Pan. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2014. [paper]

8. Structural Target Controllability of Linear Networks. Czeizler E , Wu K C , Gratie C , et al. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2018. [paper]

9. Designing pinning network controllability for interdependent dynamical network. Rasoul Rajaei, Abdolmahdi Bagheri, Amin Ramezani, Sean P. Cornelius, Jianxi Gao. IEEE 2018 Annual American Control Conference, 2018. [paper]

10. Stability analysis of large-scale networked control systems with local networks a hybrid small-gain approach. Borgers D P , Heemels M W P M H. International Conference on Hybrid Systems: Computation & Control, 2014. [paper]

11. Statistical Mechanics of the Minimum Dominating Set Problem. Zhao J H , Habibulla Y , Zhou H J. Journal of Statistical Physics, 2015. [paper]

12. A hybrid evolutionary algorithm with guided mutation for minimum weight dominating set. Chaurasia S N , Singh A. Applied Intelligence, 2015. [paper]

13. A hybrid self-adaptive evolutionary algorithm for the minimum weight dominating set problem. Lin, Geng. International Journal of Wireless and Mobile Computing, 2016. [paper]

14. Evolvable Autonomic Management. Kamal R , Hong C S. Applied & Computational Mathematics, 2015. [paper]

15. Hybrid Genetic Algorithm for Minimum Dominating Set Problem. Hedar A R , Ismail R. Computational Science and Its Applications - ICCSA, 2010. [paper]

16. Parallel Genetic Algorithm for Minimum Dominating Set Problem. Giap C N , Ha D T. Commantel. IEEE, 2014. [paper]

17. A Hybrid Genetic Algorithm for Minimum Weight Dominating Set Problem. Ugurlu O , Tanir D. Recent Developments and the New Direction in Soft-Computing Foundations and Applications, 2018. [paper]

18. A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem. Alharbi Saad, Venkat Ibrahim. Journal of Optimization, 2017. [paper]

19. Hybrid metaheuristic algorithms for minimum weight dominating set. Potluri A , Singh A. Applied Soft Computing, 2013. [paper]

20. An Effective Hybrid Memetic Algorithm for the Minimum Weight Dominating Set Problem. Lin G , Zhu W , Ali M M. IEEE transactions on evolutionary computation, 2016. [paper]

21. A memetic algorithm for minimum independent dominating set problem. Wang Y , Chen J , Sun H , et al. Neural Computing and Applications, 2017. [paper]

22. An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks. Lin G , Guan J , Feng H. Physica A Statistical Mechanics & Its Applications, 2018. [paper]

23. Two Hybrid Meta-heuristic Approaches for Minimum Dominating Set Problem. Potluri A , Singh A. SEMCCO, 2011. [paper]

24. A Heuristic Algorithm for Minimum Connected Dominating Set with Maximal Weight in Ad Hoc Networks. Yan X , Sun Y , Wang Y. Grid and Cooperative Computing, 2003. [paper]

25. Experimental Analysis of Heuristic Algorithms for the Dominating Set Problem. Sanchis L A. Springer-Verlag New York, 2002. [paper]

26. Hybrid bat algorithm for minimum dominating set problem. Abed, Saad Adnan, Rais, Helmi Md. Journal of Intelligent & Fuzzy Systems, 2017. [paper]

27. Minimal dominating set problem studied by simulated annealing and cavity method: analytics and population dynamics. Habibulla, Yusupjan. Journal of Statistical Mechanics: Theory and Experiment, 2017. [paper]

28. Simulated annealing with stochastic local search for minimum dominating set problem. Hedar A R , Ismail R. International journal of machine learning and cybernetics, 2012. [paper]

29. A Binary Particle Swarm Optimization for the Minimum Weight Dominating Set Problem. Lin G , Guan J. 计算机科学技术学报(英文版), 2018. [paper]

30. Ant colony optimization applied to minimum weight dominating set problem. Jovanovic R , Tuba M , Simian D. World Scientific and Engineering Academy and Society, 2010. [paper]

31. An ACO Algorithm for Effective Cluster Head Selection. Sampath A , Tripti C , Thampi S M. Journal of Advances in Information Technology, 2011. [paper]

32. An artificial bee colony algorithm for minimum weight dominating set. C G Nitash, Alok Singh. IEEE Symposium On Swarm Intelligence, 2014. [paper]

33. An evolutionary algorithmic approach to construct Connected Dominating Set in MANETs. D. Manohar , G. S. Anandha Mala. International Conference on Software Engineering and Mobile Application Modelling and Development, 2012. [paper]

Influence Maximization/ Vital Node Identification

1. Influence Maximization on Social Graphs: A Survey. Li Y , Fan J , Wang Y , et al. IEEE Transactions on Knowledge & Data Engineering, 2018. [paper]

2. Evolutionary algorithm for seed selection in social influence process. Michał Weskida, Radosław Michalski. IEEE International Conference on Advances in Social Networks Analysis & Mining, 2016. [paper]

3. A new heuristic for influence maximization in social networks. Nuñez-Gonzalez J. David, Borja A , Graña Manuel, et al. Logic Journal of the lgpl, 2016. [paper]

4. A PageRank-Based Heuristic Algorithm for Influence Maximization in the Social Network. Luo Z L , Cai W D , Li Y J , et al. Recent Progress in Data Engineering and Internet Technology, 2012. [paper]

5. A Genetic NewGreedy Algorithm for Influence Maximization in Social Network. Tsai C W , Yang Y C , Chiang M C. IEEE International Conference on Systems, 2015. [paper]

6. Influence Maximization in Social Networks with Genetic Algorithms. Bucur D , Iacca G. European Conference on the Applications of Evolutionary Computation, 2016. [paper]

7. Maximizing influence in a social network: Improved results using a genetic algorithm. Zhang K , Du H , Feldman M W. Physica A Statistical Mechanics & Its Applications, 2017. [paper]

8. Social Influence Maximization Using Genetic Algorithm with Dynamic Probabilities. Agarwal S , Mehta S. Eleventh International Conference on Contemporary Computing. IEEE Computer Society, 2018. [paper]

9. Application of the Ant Colony Optimization Algorithm to Competitive Viral Marketing. Yang W S , Weng S X. Hellenic Conference on Artificial Intelligence: Theories & Applications, 2012. [paper]

10. Discrete particle swarm optimization based influence maximization in complex networks. Wang Q , Gong M , Song C , et al. IEEE Congress on Evolutionary Computation, 2017. [paper]

11. Influence maximization in social networks based on discrete particle swarm optimization. Gong M , Yan J , Shen B , et al. Information Sciences, 2016. [paper]

12. Simulated Annealing Based Influence Maximization in Social Networks. Jiang Q , Song G , Cong G , et al. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011. [paper]

13. An Effective Simulated Annealing for Influence Maximization Problem of Online Social Networks. Shi-Jui, Liu, Chi-Yuan, et al. Procedia Computer Science, 2017. [paper]

14. Positive influence maximization in signed social networks based on simulated annealing. Li D , Wang C , Zhang S , et al. Neurocomputing, 2017. [paper]

15. DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks. Cui L , Hu H , Yu S , et al. Journal of network and computer applications, 2018. [paper]

16. Optimal percolation on multiplex networks. Osat S , Faqeeh A , Radicchi F. Nature Communications, 2017. [paper]

17. Influence maximization in complex networks through optimal percolation. Flaviano, Morone, Hernán, A, & Makse. Nature, 2015. [paper]

18. Applying local search to the feedback vertex set problem. Philippe Galinier, Eunice Lemamou, Mohamed Wassim Bouzidi. Journal of Heuristics, 2013. [paper]

19. Solving the undirected feedback vertex set problem by local search. Qin S M , Zhou H J. The European Physical Journal B, 2014. [paper]

20. Detecting critical nodes in sparse graphs. Ashwin Arulselvan, Clayton W. Commaner, Lily Elefteriadou, Panos M. Pardalos. Computers and Operations Research, 2009. [paper]

21. Collective Influence Algorithm to find influencers via optimal percolation in massively large social media. Morone F , Min B , Bo L , et al. Scientific Reports, 2016. [paper]

Transportation

1. Multi-Objective Fixed-Charge Transportation Problem with Random Rough Variables. Roy, Sankar Kumar,Midya, Sudipta,Yu, Vincent F. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2018. [paper]

2. DA Memetic Algorithm for Routing in Urban Public Transportation Networks. Jolanta Koszelew, Krzysztof Ostrowski. nternational Conference. DBLP, 2011. [paper]

3. Green transportation scheduling with pickup time and transport mode selections using a novel multi-objective memetic optimization approach. Guo, Zhaoxia, Zhang, et al. Transportation Research Part D Transport & Environment, 2018. [paper]

4. Transportation Cloud Service Composition Based on Fuzzy Programming and Genetic Algorithm. Zhang Weibin, Guo Haifeng, Zeng Ziqiang, Qi Yong, Wang Yinhai. Transportation Research Record Journal of the Transportation Research Board, 2018. [paper]

5. Investment in Transportation Network Capacity Under Uncertainty_ Simulated Annealing Approach. Sun Y , Turnquist M. Transportation Research Record Journal of the Transportation Research Board, 2007. [paper]

6. Regional Land Use and Transportation Planning with a Genetic Algorithm. Balling, Richard, Lowry, Michael, Saito, Mitsuru. Transportation Research Record: Journal of the Transportation Research Board, 2003. [paper]

7. Memetic Algorithm for Computing Shortest Paths in Multimodal Transportation Networks. Dib O , Manier M A , Caminada A. Transportation Research Procedia, 2015. [paper]

8. Optimization of Transit Priority in the Transportation Network Using a Genetic Algorithm. Mesbah M, Sarvi M, Currie G. IEEE Transactions on Intelligent Transportation Systems, 2011. [paper]

9. A Hybrid Genetic Algorithm for Solving Single-Stage Fixed-Charge Transportation Problems. Raj K A A D , Rajendran C. Technology Operation Management, 2011. [paper]

10. An ant colony system for transportation user equilibrium analysis in congested networks. Matteo Matteucci, Lorenzo Mussone. Swarm Intelligence, 2013. [paper]

11. Multi-objective Solid Transportation Problem in Uncertain Environment. Dalman, Hasan, Sivri, Mustafa. Iranian Journal of Science and Technology, Transactions A: Science, 2017. [paper]

12. Multi-objective solid transportation problem under stochastic environment. Singh S , Pradhan A , Biswal M P. Sadhana, 2019. [paper]

13. A new multi-objective model of agile supply chain network design considering transportation limits. Mahmoodi, Mahdi. Production & Manufacturing Research, 2019. [paper]

14. Scheduling job shop with lot streaming and transportation through a modified artificial bee colony. Lei Deming, Guo Xiuping. International Journal of Production Research, 2013. [paper]

15. Simulated Annealing Approach for Transportation Problem of Cross-docking Network Design. İlker Küçükoğlua, Nursel Öztürka. Procedia Social and Behavioral Sciences, 2014. [paper]

16. Ant colony system based routing and scheduling for hazardous material transportation. Rojee Pradhananga, Eiichi Taniguchi, Tadashi Yamada. Procedia - Social and Behavioral Sciences, 2010. [paper]

17. A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing. Zhaoxia Guo, Leyuan Shi, Longchao Chen, Yong Liang. Omega, 2017. [paper]

18. A memetic algorithm for the patient transportation problem. Zhang Z , Liu M , Lim A. Omega, 2015. [paper]

19. Memetic algorithms for solving a bi-objective Transportation Location Routing Problem. Iris Martínez-Salazar, Julián Molina, Rafael Caballero, Francisco Ángel-Bello. Proceedings of the Industrial and Systems Engineering Research Conference, 2014. [paper]

20. Container Swap Trailer Transportation Routing Problem Based on Genetic Algorithm. Ma H W , Tao L , Hu X X. Mathematical Problems in Engineering, 2018. [paper]

21. On the simulated annealing adaptation for tasks transportation optimization. Burduk A , Bożejko, Wojciech, Pempera, Jarosław, et al. Logic Journal of Igpl, 2018. [paper]

22. Emergency materials transportation model in disasters based on dynamic programming and ant colony optimization. Jia Liu， Xie Kefan. Kybernetes, 2017. [paper]

23. Multi-objective model of waste transportation management for crude palm oil industry. Silalahi, Meslin, Mawengkang, Herman, Syahputri, Nenna Irsa. IOP Conference Series: Materials Science and Engineering, 2018. [paper]

24. Fuzzy scheduling optimization system for multi-objective transportation path based on ant colony algorithm. Wu Gengrui, Bo Niao, Wu Husheng, Yang Yong, Hassan Nasruddin. Journal of Intelligent & Fuzzy Systems, 2018. [paper]

25. Multidisciplinary design optimization of space transportation control system using genetic algorithm. Jafar Roshanian, Masoud Ebrahimi, Ehsan Taheri, & Ali Asghar Bataleblu. neurología, 2013. [paper]

26. Transportation network user equilibrium assignment by ant colony systems with a variable trail decay coefficient. Matteucci, Matteo, Mussone, Lorenzo, Ghozia, Ahmed. IFAC Proceedings, 2009. [paper]

27. Handicapped Person Transportation_ An application of the Grouping Genetic Algorithm. Rekiek B , Delchambre A , Saleh H A. Engineering Applications of Artificial Intelligence, 2006. [paper]

28. Estimating transportation energy demand in Turkey using the artificial bee colony algorithm. Sonmez M , Akgungor A P , Bektas S. Energy, 2017. [paper]

29. Refuse Collection and Transportation Plan by Genetic Algorithm. Fujino, Kazunori. Doboku Gakkai Ronbunshu, 1997. [paper]

30. A Tabu Search Heuristic for the Inland Container Transportation Problem. Sterzik, Sebastian, Kopfer, Herbert. Computers & Operations Research, 2013. [paper]

31. Solving transportation problems with nonlinear side constraints with tabu search. Cao B , Uebe. Computers & Operations Research, 1995. [paper]

32. A priority based genetic algorithm for nonlinear transportation costs problems. Farhad Ghassemi Tari , Zahra Hashemi. Computers & Industrial Engineering, 2016. [paper]

33. Nonlinear fixed charge transportation problem by minimum cost flow-based genetic algorithm. Xie F , Jia R. Computers & Industrial Engineering, 2012. [paper]

34. Optimization of natural gas pipeline transportation using ant colony optimization. Chebouba A , Yalaoui F , Smati A , et al. Computers & operations research, 2009. [paper]

35. Addressing a nonlinear fixed-charge transportation problem using a spanning tree-based genetic algorithm. Hajiaghaei-Keshteli M , Molla-Alizadeh-Zavardehi S. Computers & Industrial Engineering, 2010. [paper]

36. Nonlinear fixed charge transportation problem by spanning tree-based genetic algorithm. Jo J B , Li Y , Gen M. Computers & Industrial Engineering, 2007. [paper]

37. Bicriteria Transportation Problem by Hybrid Genetic Algorithm. Gen M , Ida K , Li Y. Computers & Industrial Engineering, 1998. [paper]

38. A genetic algorithm for the generalised transportation problem. Ho W, Ji P. International Journal of Computer Applications in Technology, 2005. [paper]

39. Ant colony optimization algorithms for solving transportation problems. Kazharov A A , Kureichik V M. Journal of Computer & Systems Sciences International, 2010. [paper]

40. Multi-objective two-stage grey transportation problem using utility function with goals. Roy, Sankar Kumar, Maity, Gurupada, Weber, Gerhard-Wilhelm. Central European Journal of Operations Research, 2017. [paper]

41. Weather routing for offshore transportation using genetic algorithm. Kim B , Kim T W. Applied Ocean Research, 2017. [paper]

42. Path Optimization of Container Multimodal Transportation Based on Improved Genetic Algorithm. Li J , Yang Y F , Liu H. Applied Mechanics & Materials, 2013. [paper]

43. Optimization for Coal Heavy Haul Transportation Assembly Scheme Problem Using Genetic Algorithm. Xuesong Han, Zhenghong Gu. Applied Mechanics and Materials, 2013. [paper]

44. The Research on the Optimization of Transportation Routing for Fresh Food by Improved Genetic Algorithm. Wu Y , Meng Z B , Peng M. Applied Mechanics & Materials, 2012. [paper]

45. Cooperative particle swarm optimization for multiobjective transportation planning. Zheng Y J , Chen S Y. Applied Intelligence, 2013. [paper]

46. Greening of maritime transportation_ a multi-objective optimization approach. Cheaitou, Ali, Cariou, Pierre. Annals of Operations Research, 2018. [paper]

47. Multiobjective Optimization for Multimode Transportation Problems. Laurent L , Massé Damien, Pascal R , et al. Advances in Operations Research, 2018. [paper]

48. A multi objective solid transportation problem in fuzzy bi-fuzzy environment via genetic algorithm. Sutapa Pramanik, D.K. Jana, K. Maity. International Journal of Advanced Operations Management, 2014. [paper]

49. Prediction of Short-Term Transportation Flow Based on Optimizing Wavelet Neural Network by Genetic Algorithm. Yang Sheng Long, Ma Jun Jie, Wang Cui Hua, Zhang Sheng Ma. Advanced Materials Research, 2013. [paper]

50. Solving logistics transportation based on improved genetic algorithm. Ma Z , Liu F. Sixth International Conference on Natural Computation. IEEE, 2010. [paper]

51. Design A Routing-Allocation Model for Relief Transportation of the Earthquake Wounded Using Simulated Annealing Method. Seyed Rasoul Hosseini Baharanchi, Masoud Mosadeg Khah, Gholamreza Jandaghi. EuroJournals, Inc. 2011. [paper]

Game Theory

1. Research on Doctor-Patient Relationship Based on Evolutionary Game Theory. Chen Miao, Su Qiang. 16th International Conference on Service Systems and Service Management, 2019. [paper]

2. Evolutionary Game Theory Based Network Selection for Constrained Heterogeneous Networks. Nannan Sui, Dongmei Zhang, Wei Zhong, Lianguo Wu, Zhensong Zhang. International Conference on Information Science and Control Engineering, 2015.

3. Evidence Combination From an Evolutionary Game Thery Perspective. Deng X , Han D , Dezert J , et al. IEEE Transactions on Cybernetics, 2016. [paper]

4. An Evolutionary Game Theoretic Analysis of Difference Evaluation Functions. Mitchell Colby, Kagan Tumer. Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015. [paper]

5. Theory and use case of game-theoretic lexical link analysis. Zhao Y , Zhou C C D , Huang S. The 2019 IEEE International Conference on ASONAM, 2019. [paper]

6. Review of Game Theory, Alive. Aazami A B. Acm Sigact News, 2018. [paper]

7. A Generalised Method for Empirical Game Theoretic Analysis. Karl Tuyls, Julien Perolat, Marc Lanctot, Joel Z Leibo, Thore Graepel. Computer Science and Game Theory, 2018. [paper]

8. Approximate game theoretic analysis for large simulation-based games. Bryce Wiedenbeck. Proceedings of the 2014 international conference on Autonomous agents and multi-agent systemsMay, 2014. [paper]

Biological Network Research Direction

1. Global Alignment of Protein-Protein Interaction Networks-A Survey. Elmsallati A , Clark C , Kalita J. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

2. Global Biological Network Alignment by Using Efficient Memetic Algorithm. Maoguo Gong , Zhenglin Peng , Lijia Ma. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

3. Multiple Network Alignment via MultiMAGNA++. Vijayan V , Milenkovic T. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

4. A Global Network Alignment Method Using Discrete Particle Swarm Optimization. Huang J , Gong M , Ma L. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

5. A Novel Computational Approach for Global Alignment for Multiple Biological Networks. Djeddi, Warith Eddine, Ben Yahia, Sadok, Nguifo, Engelbert. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018. [paper]

6. An adaptive hybrid algorithm for global network alignment. Xie J , Xiang C , Ma J , et al. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2015. [paper]

7. Active Network Alignment A Matching-Based Approach. Malmi E , Gionis A , Terzi E. Proceedings of the 2017 ACM on Conference on Information and Knowledge ManagementNovember, 2017. [paper]

8. Triangular Alignment (TAME): A Tensor-based Approach for Higher-order Network Alignment. Shahin Mohammadi, David Gleich, Tamara Kolda, Ananth Grama. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017. [paper]

9. Comprehensive Updates in Network Synthesis Models to Create An Improved Benchmark for Network Alignment Algorithms. Hyundoo Jeong, Byung-Jun Yoon. BMC Systems Biology, 2018. [paper]

10. Multiple Biological Network Alignment through Network Generation and Feature Weight Annotations. Kiran K, Girisha M N, Santosh Pattar, P Deepa Shenoy, Venugopal K R. IEEE International Conference on Electronics, Computing and Communication Technologies, 2019. [paper]

11. Survey of biological network alignment cross-species analysis of conserved systems. Sawal Maskey, Young-Rae Cho. IEEE International Conference on Bioinformatics and Biomedicine, 2019. [paper]

12. Fair evaluation of global network aligners. Crawford J , Sun Y , Tijana Milenković. Algorithms for Molecular Biology, 2014. [paper]

13. GMAlign A new network aligner for revealing large conserved functional components. Yuanyuan Zhu , Yuezhi Li , Juan Liu. IEEE International Conference on Bioinformatics & Biomedicine, 2017. [paper]

14. Genetic Algorithm for Optimizing Global Alignment of Protein-Protein Interaction Network. Qanita Bani Baker, Manar K Al-Bataineh. CIBCB, 2019.

15. MAGNA++ Maximizing Accuracy in Global Network Alignment via both node and edge conservation. Vijayan V , Saraph V , Milenkovi T. Bioinformatics, 2015. [paper]

16. SANA: simulated annealing far outperforms many other search algorithms for biological network alignment. Nil Mamano, Wayne Brian Hayes. Bioinformatics, 2017. [paper]

17. Detecting Protein Complexes from Signed Protein-Protein Interaction Networks. Ou Yang L , Dai D Q , Zhang X F. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2015. [paper]

18. A new method for detecting protein complexes based on the three node cliques. Zhang W , Zou X. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2015. [paper]

19. Protein Complex Detection via Effective Integration of Base Clustering Solutions and Co-Complex Affinity Scores. Wu M , Ou-Yang L , Li X L. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

20. Evolutionary Graph Clustering for Protein Complex Identification. He T , Chan K C C. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

21. Measuring Boundedness for Protein Complex Identification in PPI Networks. He T , Chan K C C. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2018. [paper]

22. United Complex Centrality for Identification of Essential Proteins from PPI Networks. Li M , Lu Y , Niu Z , et al. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2017. [paper]

23. The intrinsic geometric structure of protein-protein interaction networks for protein interaction prediction. Fang, Yi, Sun, Mengtian, Dai, Guoxian, Ramain, Karthik. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016. [paper]

24. Protein-Protein Complex Interface Interacting Residue Pairs Prediction Using Deep Learning Approach. Zhao Z , Gong X. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2017. [paper]

25. Detecting Protein Complexes Based on Uncertain Graph Model. Bihai, Zhao, Jianxin, et al. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2014. [paper]

26. Three-Dimensional Protein Structure Prediction Based on Memetic Algorithms. Corrêa, Leonardo, de, Lima, Borguesan, & Bruno, et al. Computers & Operations Research, 2017. [paper]

27. Protein Structure Optimization with a "Lamarckian"" Ant Colony Algorithm. Oakley M T , Richardson E G , Carr H , et al. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2013. [paper]

28. Protein complexes predictions within protein interaction networks using genetic algorithms. Ramadan E , Naef A , Ahmed M. Bmc Bioinformatics, 2016. [paper]

Recommendation System/ Link Prediction

1. A Hybrid Course Recommendation System by Integrating Collaborative Filtering and Artificial Immune Systems. Pei Chann C , Cheng Hui L , Meng Hui C. Algorithms, 2016. [paper]

2. A link prediction algorithm based on ant colony optimization. Chen B , Chen L. Applied Intelligence, 2014. [paper]

3. Microblog user recommendation based on particle swarm optimization. Xing L , Ma Q , Jiang L. 中国通信, 2017. [paper]

4. An evolutionary algorithm approach to link prediction in dynamic social networks. Catherine A. Bliss Morgan R. Journal of Computational Science, 2014. [paper]

5. Web-Based System User Interface Hybrid Recommendation Using Ant Colony Metaphor. Janusz Sobecki. Lecture Notes in Computer Science, 2007. [paper]

6. Student Courses Recommendation Using Ant Colony Optimization. Sobecki J , Tomczak J M. Intelligent Information and Database Systems, Second International Conference, 2010. [paper]

7. An attribute-based ant colony system for adaptive learning object recommendation. Yang Y J , Wu C. Expert Systems with Applications, 2009. [paper]

8. Artificial immune system-based music recommendation. Sotiropoulos D N , Tsihrintzis G A. Intelligent Decision Technologies, 2018. [paper]

9. Memetic algorithm based location and topic aware recommender system. Shanfeng Wang, Maoguo Gong, Haoliang Li, Junwei Yang, Yue Wu. Knowledge-Based Systems, 2017. [paper]

10. Movie recommender system with metaheuristic artificial bee. Katarya, Rahul. Neural Computing & Applications, 2018. [paper]

11. Ant Colony Metaphor Applied in User Interface Recommendation. Janusz Sobecki. New Generation Computing, 2008. [paper]

12. A novel multi-objective evolutionary algorithm for recommendation systems. Laizhong Cui, Peng Ou, Xianghua Fu, Zhenkun Wen, & Nan Lu. Journal of Parallel and Distributed Computing, 2016. [paper]

13. EEG based automatic music recommendation system using ranking deep artificial neural network. Hiroki I , Yoshikazu W , Yuko U. Pathophysiology, 2018. [paper]

14. Structural link prediction based on ant colony approach in social networks. EhsanSherkat, Maseud Rahgozar, Masoud Asadpour. Physica A: Statistical Mechanics and its Applications, 2015. [paper]

15. Link Prediction based on Quantum-Inspired Ant Colony Optimization. Zhiwei C , Yichao Z , Jihong G , et al. Scientific Reports, 2018. [paper]

16. Social Recommendation With Evolutionary Opinion Dynamics. Fei X , Ximeng W , Shirui P , et al. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018. [paper]

17. A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm. Chunhua J , Chonghuan X. Scientific World Journal, 2013. [paper]

18. Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization. WANG Xibin, LUO Fengji, SANG Chunyan, ZENG Jun, HIROKAWA, Sachio. IEICE Transactions on Information and Systems, 2017. [paper]

19. A hybrid recommendation algorithm–based intelligent business recommendation system. Yang F. Journal of Discrete Mathematical Sciences and Cryptography, 2018. [paper]

20. TCARS: Time- and Community-Aware Recommendation System. Rezaeimehr, Fatemeh, Moradi, et al. Future Generations Computer Systems Fgcs, 2018. [paper]

SIR/SIS Propagation

Immunization

1. Two Models of Immunization for Time Dependent Optimization. A. Gaspar and P. Collard. IEEE International Conference on Systems, 2000. [paper]

2. A detector evolution algorithm based on Immunization Strategy of Complex Networks. C. Shi, H. Zhao and H. Shi. IEEE International Conference on Signal Processing, Communications and Computing, 2014. [paper]

3. A model for designing callable bonds and its solution using tabu search. Consiglio A , Zenios S A. Journal of Economic Dynamics & Control, 1997. [paper]

4. Developing a vaccination evaluation model to support evidence-based decision making on national immunization programs. Kimman TG, Boot HJ, Berbers GA, Vermeer-de Bondt PE, Ardine de Wit G, de Melker HE. Vaccine, 2006. [paper]

5. Edges Immunization Strategy Based on Discrete PSO in Weighted Scale-Free Network. LIN Bing, GUO Wenzhong, CHEN Guolong. IEEE Sixth International Conference on Innovative Mobile & Internet Services in Ubiquitous Computing, 2012. [paper]

6. Evolutionary Algorithm for Optimal Vaccination Scheme. Parousis-Orthodoxou K J , Vlachos D S. Journal of Physics Conference, 2014. [paper]

7. Immunization of Networks Using Genetic Algorithms and Multiobjective Metaheuristics. A. Maulana, M. Kefalas and M. T. M. Emmerich. IEEE Symposium Series on Computational Intelligence, 2017. [paper]

8. Immunization Strategy with Particle Swarm Optimization for Virus Spread Control in Weighted Scale-Free Networks. Wen Zhong G , Guo Long C , Ning Ning W , et al. Pattern Recognition and Artificial Intelligence, 2013. [paper]

9. Improving the oral immunization of foxes (Vulpes vulpes) against rabies with the help of an evolutionary algorithm. Selhorst T. Ecological Modelling, 2000. [paper]

10. Targeted Local Immunization in Scale-Free Peer-to-Peer Networks. Huang X L , Zou F T , Ma F Y. 计算机科学技术学报(英文版), 2007. [paper]

11. Node Immunization over Infectious Period. Song C , Hsu W , Lee M L. the 24th ACM International, 2015. [paper]

12. An Efficient Immunization Strategy Using Overlapping Nodes and Its Neighborhoods. Manish Kumar, Anurag Singh, Hocine Cherif. ACM Press Companion of the The Web Conference, 2018. [paper]

13. A new immunization algorithm based on spectral properties for complex networks. Zahedi R , Khansari M. IEEE Conference on Information & Knowledge Technology, 2015. [paper]

14. Immunization against Infection Propagation in Heterogeneous Networks. Abbas W , Bhatia S , Vorobeychik Y , et al. IEEE International Symposium on Network Computing & Applications, 2014. [paper]

15. A VEIS computer virus propagation model based on partly immunization. Sun Zhiqiang, Chen Liang, Chen Qiaoling. ACM Press the 2016 International Conference, 2016. [paper]

16. Propagation and immunization in large networks. Prakash B A. Crossroads, 2012. [paper]

17. Epidemic spreading and immunization strategy in multiplex networks. Zuzek L G A , Buono C , Braunstein L A. Journal of Physics Conference Series, 2015. [paper]

18. Immunization of complex networks. Pastor-Satorras, Romualdo, Vespignani, Alessandro. Physical Review E, 2002. [paper]

19. Immunization strategy for epidemic spreading on multilayer networks. Buono C , Braunstein L A. Epl, 2015. [paper]

Privacy Protection

1. PRAM Optimization Using an Evolutionary Algorithm. Jordi Marés, Vicenç Torra. Privacy in Statistical Databases-unesco Chair in Data Privacy, International Conference, 2010. [paper]

2. An evolutionary algorithm to enhance multivariate Post-Randomization Method (PRAM) protections. Marés, Jordi, Torra V. Information Sciences, 2014. [paper]

3. Data privacy using an evolutionary algorithm for invariant PRAM matrices. Marés, Jordi, Shlomo N. Computational Statistics & Data Analysis, 2014. [paper]

4. An evolutionary approach to enhance data privacy. Javier Jiménez, Jordi Marés, Torra V. Soft Computing, 2011. [paper]

5. An evolutionary optimization approach for categorical data protection. Jordi Marés and Vicenç Torra. ICPS, 2012. [paper]

6. Privacy Protection with Genetic Algorithms. Solanas A. 1970. [paper]

7. Fractal Intelligent Privacy Protection in Online Social Network Using Attribute-Based Encryption Schemes. Wei W , Shuai L , Wenjia L , et al. IEEE Transactions on Computational Social Systems, 2018. [paper]

8. An Evaluation of the Current State of Genomic Data Privacy Protection Technology and a Roadmap for the Future. Malin B A. Journal of the American Medical Informatics Association, 2005. [paper]

9. Evolutionary approach to violating group anonymity using third-party data. Tavrov Dan, Chertov Oleg. Springerplus, 2016. [paper]

10. Traffic-Aware Multiple Mix Zone Placement for Protecting Location Privacy. Liu X , Zhao H , Pan M , et al. Proceedings IEEE Infocom, 2012. [paper]

11. Personalized Anonymization for Set-Valued Data by Partial Suppression. Nakagawa T , Arai H , Nakagawa H. IEEE International Conference on Data Mining Workshops, 2017. [paper]

12. Research on Classification of Privacy Protection Based on Improved Particle Swarm Optimization Algorithm. Chen Y , Tang Y X , Zhou Z. Applied Mechanics & Materials, 2014. [paper]

13. User-Centric Multiobjective Approach to Privacy Preservation and Energy Cost Minimization in Smart Home. Chang Hsuan-Hao, Chiu Wei-Yu, Sun Hongjian, Chen Chia-Ming. IEEE Systems Journal, 2018. [paper]

14. Privacy-Preserving Tabu Search for Distributed Graph Coloring. Hong Y , Vaidya J , Lu H , et al. IEEE Third International Conference on Passat/socialcom, 2011. [paper]

15. Multiple-negative survey method for enhancing the accuracy of negative survey-based cloud data privacy: Applications and extensions. Liu R , Peng J , Tang S. Engineering Applications of Artificial Intelligence, 2017. [paper]

16. Transforming Data to Satisfy Privacy Constraints. Vijay S. lyengar. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002. [paper]

17. Guaranteeing Anonymity when Sharing Medical Data,the Datafly System. *Proceedings of the Amia Annual Fall Symposium, 1997. [paper]

18. Multiple Mix-Zones Deployment for Continuous Location Privacy Protection. Xu Z , Zhang H , Yu X. IEEE Trustcom/Bigdatase/Ispa, 2017. [paper]

19. Privacy-Optimal Coordination of Protection Relays Using New Hybrid Evolutionary Algorithm. Chunlin Xu, Xiufen Zou, Rongxiang Yuan, et al. IEEE Evolutionary Computation, 2008. [paper]

20. A Hybrid Genetic Algorithm for Privacy and Cost Aware Scheduling of Data Intensive Workflow in Cloud. Chen C , Liu J , Wen Y , et al. Algorithms and Architectures for Parallel Processing, 2015. [paper]

21. An evolutionary approach to enhance data privacy. Javier Jiménez, Jordi Marés, Torra V. Soft Computing, 2011. [paper]

22. Privacy Preserving Fuzzy Association Rule Mining in Data Clusters Using Particle Swarm Optimization. Krishnamoorthy S , Sadasivam G S , Rajalakshmi M , et al. International Journal of Intelligent Information Technologies, 2017. [paper]

23. Privacy preserving association rule mining over distributed databases using genetic algorithm. Keshavamurthy B N , Khan A M , Toshniwal D. Neural Computing & Applications, 2013. [paper]

Network Representation

1. A model for virtual network embedding using Artificial Bee Colony. Pathak I , Tripathi A , Vidyarthi D P. International Journal of Communication Systems, 2018. [paper]

2. Virtual network embedding with discrete particle swarm optimisation. Guo Y , Wang L , Zhao J , et al. Electronics Letters, 2014. [paper]

3. Memetic Elitist Pareto Evolutionary Algorithm for Virtual Network Embedding. Shahin A A. Computer & Information Science, 2015. [paper]

4. A model for virtual network embedding across multiple infrastructure providers using genetic algorithm. Pathak I , Vidyarthi D P. Science China, 2017. [paper]

5. A Virtual Network Embedding Algorithm Based on Cellular Automata Genetic Mechanism. Lei Zhuang, Guoqing Wang, Ming Wang, Kunli Zhang. International Conference on Electronic Information Technology and Computer Engineering, 2018. [paper]

6. Adaptive multi-objective artificial immune system based virtual network embedding. Zhang Z , Su S , Lin Y , et al. Journal of Network & Computer Applications, 2015. [paper]

7. Virtual network embedding based on modified genetic algorithm. Zhang P , Yao H , Li M , et al. Peer to Peer Networking & Applications, 2017. [paper]

8. Community Preserving Network Embedding Based on Memetic Algorithm. Maoguo G , Cheng C , Yu X , et al. IEEE Transactions on Emerging Topics in Computational Intelligence, 2018. [paper]

9. Optimal virtual network embedding based on artificial bee colony. Liu X , Zhang Z , Li X , et al. EURASIP Journal on Wireless Communications and Networking, 2016. [paper]

10. Multi-objective enhanced particle swarm optimization in virtual network embedding. Zhang P , Yao H , Fang C , et al. Eurasip Journal on Wireless Communications and Networking, 2016. [paper]

11. Network reconstruction based on time series via memetic algorithm. Wu K , Liu J , Chen D. Knowledge Based Systems, 2018. [paper]

12. Network Representation Learning: A Survey. Daokun Z , Jie Y , Xingquan Z , et al. IEEE Transactions on Big Data, 2018. [paper]