Author: Zohreh Raziei
The quadratic assignment problem (QAP) is one member of the NP-hard class of combinatorial optimization problems. It is difficult to solve it in the polynomial-time, even for small instances. Research on the QAP has thus focused on obtaining a method to overcome this problem. The goal of this paper is to compare and analyze the performance of the different Evolutionary Algorithm (EV) and Swarm Intelligence (SI) meta-heuristics with Local Search Heuristic (LSH) that is based on 2-Opt heuristics. The EA included the Genetic Algorithm (GA) and Harmony Search (HS), and SI included Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Gray Wolf Optimization (GWO). Also, the Hybrid GA-PSO is considered in the comparison. The problem instances of QAPLIB are used to evaluate the performance of the algorithm on QAP.
Code from my paper "Performance Analysis of Meta-heuristic Algorithms for aQuadratic Assignment Problem".