Job shop scheduling based on ACO with a hybrid solution construction strategy

This paper presents a novel ant colony optimization (ACO) based on an efficient solution construction strategy (transition operator) for improving the quality of the end results of job shop scheduling problem (JSSP). Inspired by the observation that the quality of the end results of ACO is largely a...

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Bibliographic Details
Main Authors: Shih-Pang Tseng, Chun-Wei Tsai, Jui-Le Chen, Ming-Chao Chiang, Chu-Sing Yang
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Ant colony optimization
Benchmark testing
Electronic mail
Job shop scheduling
job shop scheduling problem
Optimization
Simulation
transition operator
Online Access:Request full text
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Summary:This paper presents a novel ant colony optimization (ACO) based on an efficient solution construction strategy (transition operator) for improving the quality of the end results of job shop scheduling problem (JSSP). Inspired by the observation that the quality of the end results of ACO is largely affected by their operators-especially the transition operator, a novel solution construction strategy is presented in this paper. The proposed algorithm uses two different strategies to compute the probability of solution construction to improve the end results. Our experimental results show that the proposed algorithm outperforms all state-of-the-art job shop scheduling algorithms evaluated in this paper and can significantly improve the quality of ant colony optimization for JSSP.
ISSN:1098-7584
DOI:10.1109/FUZZY.2011.6007565