4.5 Article

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

期刊

COMPUTERS & OPERATIONS RESEARCH
卷 36, 期 7, 页码 2217-2229

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2008.08.015

关键词

Ant colony optimization; MINLP; Global optimization; Hybrid metaheuristics; Constrained optimization; Oracle penalty method

资金

  1. Spanish Ministry of Education and Science

向作者/读者索取更多资源

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 MINLPs, is presented together with numerical results. These extensions on the ACO framework have been developed to serve the needs of practitioners who face highly non-convex and computationally costly MINLPs. The performance of this new method is evaluated considering several non-convex MINLP benchmark problems and one real-world application. The results obtained by our implementation substantiate the success of this new approach. (C) 2008 Elsevier Ltd. All rights reserved.

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