HYBRID CODING PSO-ACO CO-EVOLUTIONARY ALGORITHM FOR SOLVING MIXED-INTEGER PROGRAMMING PROBLEMS

Yuelin Gao () and Miaomiao Wang ()
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Yuelin Gao: School of Information and Computation Science, Beifang University for Nationalities, Yinchuan, 750021, P. R. China
Miaomiao Wang: School of Information and Computation Science, Beifang University for Nationalities, Yinchuan, 750021, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2013, vol. 30, issue 03, 1-13

Abstract: A co-evolutionary algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) is given to solve the bound constrained mixed-integer programming problem (BCMIP). For the specificity of the problem, the hybrid coding includes the real coding and the integer coding. The real coding part is evolved by PSO while the integer coding part is evolved by ACO. The entire population is co-evolved by PSO and ACO. Numerical experiments show that the proposed algorithm is feasible and effective to solve BCMIP. We also obtain satisfactory result to solve MIP when the proposed algorithm is combined with penalty function method.

Keywords: Mixed-integer programming (MIP); particle swarm optimization (PSO); ant colony optimization (ACO); co-evolutionary; hybrid coding (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0217595913400010

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