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Social Cognitive Optimization (SCO) for Constrained Numerical Optimization Problem
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Social Cognitive Optimization (SCO)

SCO is a population-based metaheuristic optimization algorithm simulating the dynamic process of social cognitive theory (SCT). It can be incorporated into cooperative group optimization (CGO) system.

The SCO paper has been cited over 70 times with various applications. SCO was also implemented (by Sun Microsystems Inc.) into NLPSolver (Solver for Nonlinear Programming), an extension of Calc in Apache OpenOffice.

Problem to be Solved

It solves (constrained) numerical optimization problem (NOP) or the nonlinear programming problem (NLP):

where f(x) is the objective function and each g(x) is a constraint function to be satisfied, and c and d are constants. All the functions can be nonlinear and nonsmooth.

General information

Portal: E-MAIL: Xiao-Feng Xie

Quick start

  • Execute: Enter the directory "example", then run the file "".

  • Compile: Type "ant" to build, and the output file will be release/sco.jar.

  • See source/problem for examples of constrain and unconstrained numerial optimization problem instances.


See the Creative Commons Non-Commercial License 3.0 for more details.

Please acknowledge the author(s) if you use this code in any way.

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