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Titlebook: Advances in Multi-Objective Nature Inspired Computing; Carlos A. Coello Coello,Clarisse Dhaenens,Laetitia Book 2010 Springer-Verlag Berlin

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樓主: 灰塵
11#
發(fā)表于 2025-3-23 10:36:04 | 只看該作者
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發(fā)表于 2025-3-23 17:49:56 | 只看該作者
Book 2010ing more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems..
13#
發(fā)表于 2025-3-23 21:52:58 | 只看該作者
14#
發(fā)表于 2025-3-24 00:16:08 | 只看該作者
1860-949X to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems..978-3-642-26238-8978-3-642-11218-8Series ISSN 1860-949X Series E-ISSN 1860-9503
15#
發(fā)表于 2025-3-24 03:14:44 | 只看該作者
Oscar Emilio Pecho Yataco,Alvaro Della Bonaal validation in a multi-objective optimization context. The aim of this chapter is not to be comprehensive, but simply to touch on the main fundamental topics that are required to understand the material that is presented in the rest of the book.
16#
發(fā)表于 2025-3-24 08:08:28 | 只看該作者
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發(fā)表于 2025-3-24 13:05:36 | 只看該作者
18#
發(fā)表于 2025-3-24 16:07:44 | 只看該作者
Environmental Effects on Color Visionn genetic algorithms, variable neighborhood search and path relinking to solve the real-world motivated problem. The algorithm is tested on real world data from the province Manabí in Ecuador. The results on small instances are compared to an epsilon constraint method. Also results for medium- and large-size real-world instances are presented.
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發(fā)表于 2025-3-24 22:30:34 | 只看該作者
20#
發(fā)表于 2025-3-25 00:36:22 | 只看該作者
https://doi.org/10.1007/978-3-030-02834-3 are scarce in the multi-objective domain. In this work, we study different mechanisms in order to update the velocity of each particle with the idea of enhancing the search capabilities of multi-objective PSO algorithms. Our experiments show that some modifications help to overcoming the difficulti
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