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An Improved Time-Sensitive Metaheuristic Framework for Combinatorial Optimization

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Experimental and Efficient Algorithms (WEA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3059))

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Abstract

We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to many existing frameworks (e.g. [27]) in that it is modular enough that important components can be independently developed to create optimizers for a wide range of problems. Ours is different in many aspects. Among them are its combinatorial emphasis and the use of simulated annealing and incremental greedy heuristics. We describe several annealing schedules and a hybrid strategy combining incremental greedy and simulated annealing heuristics. Our experiments show that (1) a particular annealing schedule is best on average and (2) the hybrid strategy on average outperforms each individual search strategy. Additionally, our framework guarantees the feasibility of returned solutions for combinatorial problems that permit infeasible solutions. We, further, discuss a generic method of optimizing efficiently bottle-neck problems under the local-search framework.

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Author information

Authors and Affiliations

  1. University of Memphis, Memphis, TN, 38152, USA

    Vinhthuy Phan

  2. SUNY Stony Brook, Stony Brook, NY, 11794, USA

    Steven Skiena

Authors
  1. Vinhthuy Phan
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  2. Steven Skiena
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Universidade Federal Fluminense, Rua Passo da Pátria, 156, Bloco E, RJ 24210-240, Niterói, Brazil

    Celso C. Ribeiro

  2. Departamento de Ciência da Computação, Universidade Federal Fluminense, Niterói, RJ, Brazil

    Simone L. Martins

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© 2004 Springer-Verlag Berlin Heidelberg

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Phan, V., Skiena, S. (2004). An Improved Time-Sensitive Metaheuristic Framework for Combinatorial Optimization. In: Ribeiro, C.C., Martins, S.L. (eds) Experimental and Efficient Algorithms. WEA 2004. Lecture Notes in Computer Science, vol 3059. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24838-5_32

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  • DOI: https://doi.org/10.1007/978-3-540-24838-5_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22067-1

  • Online ISBN: 978-3-540-24838-5

  • eBook Packages: Springer Book Archive

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