NDLI: An Improved Co-evolutionary Decomposition-based Algorithm for Bi-level Combinatorial Optimization

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An Improved Co-evolutionary Decomposition-based Algorithm for Bi-level Combinatorial Optimization

Content Provider	ACM Digital Library
Author	Ben Said, Lamjed Chaabani, Abir Azzouz, Radhia Bechikh, Slim
Abstract	Several real world problems have two levels of optimization instead of a single one. These problems are said to be bi-level and are so computationally expensive to solve since the evaluation of each upper level solution requires finding an optimal solution at the lower level. Most existing works in this direction have focused on continuous problems. Motivated by this observation, we propose in this paper an improved version of our recently proposed algorithm CODBA (CO-evolutionary Decomposition-Based Algorithm), called CODBA-II, to tackle bi-level combinatorial problems. Differently to CODBA, CODBA-II incorporates decomposition, parallelism, and co-evolution within both levels: (1) the upper level and (2) the lower one, with the aim to further cope with the high computational cost of the over-all bi-level search process. The performance of CODBA-II is assessed on a set of instances of the MDVRP (Multi-Depot Vehicle Routing Problem) and is compared against three recently proposed bi-level algorithms. The statistical analysis of the obtained results shows the merits of CODBA-II from effectiveness viewpoint.
Starting Page	1363
Ending Page	1364
Page Count	2
File Format	PDF
ISBN	9781450334884
DOI	10.1145/2739482.2764701
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-07-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Parallelism. Decomposition Co-evolution Bi-level combinatorial optimization
Content Type	Text
Resource Type	Article

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