Extended ant colony optimization for non-convex mixed integer nonlinear programming

Two novel extensions for the well known ant colony optimization (ACO) framework are introduced here, which allow the solution of mixed integer nonlinear programs (MINLPs). Furthermore, a hybrid implementation ( ACOmi) based on this extended ACO framework, specially developed for complex non-convex M...

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Vydáno v:	Computers & operations research Ročník 36; číslo 7; s. 2217 - 2229
Hlavní autoři:	Schlüter, Martin, Egea, Jose A., Banga, Julio R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.07.2009 Elsevier Pergamon Press Inc
Témata:	Ant colony optimization Applied sciences Benchmarks Constrained optimization Exact sciences and technology Global optimization Hybrid metaheuristics Integer programming Mathematical programming MINLP Operational research and scientific management Operational research. Management science Optimization Oracle penalty method Studies Oracle penalty method Ant colony optimization MINLP Hybrid metaheuristics Global optimization Constrained optimization Non convex programming Global optimum Mixed integer programming Convex programming Penalty method Integer programming Heuristic method Swarm intelligence Oracle Metamodel Non convex analysis
ISSN:	0305-0548, 1873-765X, 0305-0548
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