Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
475346 | Computers & Operations Research | 2009 | 13 Pages |
Abstract
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.
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Martin Schlüter, Jose A. Egea, Julio R. Banga,