A Framework for Accelerating Metaheuristics via Pattern Reduction

Chun Wei Tsai; Shih Pang Tseng; Ming Chao Chiang; Chu Sing Yang

doi:10.1145/1830483.1830537

A Framework for Accelerating Metaheuristics via Pattern Reduction

Chun Wei Tsai, Shih Pang Tseng, Ming Chao Chiang, Chu Sing Yang

Institute of Computer and Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

This paper presents a novel framework based on the notion of pattern reduction, called Framework for Accelerating Metaheuristics via Pattern Reduction (FAMPR), to solve an intrinsic problem of metaheuristics. That is, many computations of metaheuristics during the convergence process are essentially redundant. As such, if they can be eliminated, the computation time of metaheuristics can be significantly reduced. Our experimental result shows that the proposed framework can significantly reduce the computation time of metaheuristics while limiting the loss of quality to a very small percentage.

Original language	English
Title of host publication	Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
Pages	293-294
Number of pages	2
DOIs	https://doi.org/10.1145/1830483.1830537
Publication status	Published - 2010 Aug 27
Event	12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, United States Duration: 2010 Jul 7 → 2010 Jul 11

Publication series

Name	Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10

Other

Other	12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
Country	United States
City	Portland, OR
Period	10-07-07 → 10-07-11

All Science Journal Classification (ASJC) codes

Computational Theory and Mathematics
Theoretical Computer Science

Access to Document

10.1145/1830483.1830537

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Tsai, C. W., Tseng, S. P., Chiang, M. C., & Yang, C. S. (2010). A Framework for Accelerating Metaheuristics via Pattern Reduction. In Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 (pp. 293-294). (Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10). https://doi.org/10.1145/1830483.1830537

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title = "A Framework for Accelerating Metaheuristics via Pattern Reduction",

abstract = "This paper presents a novel framework based on the notion of pattern reduction, called Framework for Accelerating Metaheuristics via Pattern Reduction (FAMPR), to solve an intrinsic problem of metaheuristics. That is, many computations of metaheuristics during the convergence process are essentially redundant. As such, if they can be eliminated, the computation time of metaheuristics can be significantly reduced. Our experimental result shows that the proposed framework can significantly reduce the computation time of metaheuristics while limiting the loss of quality to a very small percentage.",

author = "Tsai, {Chun Wei} and Tseng, {Shih Pang} and Chiang, {Ming Chao} and Yang, {Chu Sing}",

year = "2010",

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note = "12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 ; Conference date: 07-07-2010 Through 11-07-2010",

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Tsai, CW, Tseng, SP, Chiang, MC & Yang, CS 2010, A Framework for Accelerating Metaheuristics via Pattern Reduction. in Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10, pp. 293-294, 12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010, Portland, OR, United States, 10-07-07. https://doi.org/10.1145/1830483.1830537

A Framework for Accelerating Metaheuristics via Pattern Reduction. / Tsai, Chun Wei; Tseng, Shih Pang; Chiang, Ming Chao; Yang, Chu Sing.

Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. 2010. p. 293-294 (Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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