Presentation 1996/5/24
Scheduling by Genetic Local Search with Multi-Step Crossover
Takeshi YAMADA, Ryohei NAKANO,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, multi-step crossover (MSX) and a local search method are unified into a single operator called MSXF. MSXF utilizes a neighborhood structure and a distance measure in the search space. In MSXF, a solution, initially set to be one of the parents, is stochastically replaced by a relatively good solution in the neighborhood, where the replacement is biased toward the other parent. This process is repeated until reaching the other parent, and the best solution generated in the process is selected as an offspring. Using job-shop scheduling problem (JSSP) benchmarks, MSXF was evaluated in a GA framework as a high-level crossover working on the critical path of a schedule. Experiments showed the promising performance of MSXF/GA.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Genetic Algorithms / multi-step crossover / job-shop scheduling / neighborhood search
Paper # AI96-2
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Conference Information
Committee AI
Conference Date 1996/5/24(1days)
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Paper Information
Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Scheduling by Genetic Local Search with Multi-Step Crossover
Sub Title (in English)
Keyword(1) Genetic Algorithms
Keyword(2) multi-step crossover
Keyword(3) job-shop scheduling
Keyword(4) neighborhood search
1st Author's Name Takeshi YAMADA
1st Author's Affiliation NTT Communication Science Laboratories()
2nd Author's Name Ryohei NAKANO
2nd Author's Affiliation NTT Communication Science Laboratories
Date 1996/5/24
Paper # AI96-2
Volume (vol) vol.96
Number (no) 77
Page pp.pp.-
#Pages 8
Date of Issue