A New Hybrid Ant Colony Optimization Algorithm for Permutation Flow-Shop Scheduling

Xiao Xia Zhang; Shao Qiang Liu; Yun Yong Ma

doi:10.4028/www.scientific.net/AMR.694-697.2691

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697A New Hybrid Ant Colony Optimization Algorithm for...

A New Hybrid Ant Colony Optimization Algorithm for Permutation Flow-Shop Scheduling

Abstract:

This paper presents a novel hybrid ant colony optimization approach (ACO&PR) to solve the permutation flow-shop scheduling (PFS). The main feature of this hybrid algorithm is to hybridize the solution construction mechanism of the ACO with path relinking (PR), an evolutionary method, which introduces progressively attributes of the guiding solution into the initial solution to obtain the high quality solution. Moreover, the hybrid algorithm considers both solution diversification and solution quality, and it adopts the dynamic updating strategy of the reference set to accelerate the convergence towards high-quality regions of the search space. Finally, the experimental results for benchmark PFS instances have shown that our proposed method is very efficient to solve the permutation flow-shop scheduling compared with the best existing methods in terms of solution quality.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

2691-2694

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.2691

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Online since:

May 2013

Authors:

Xiao Xia Zhang*, Shao Qiang Liu, Yun Yong Ma

Keywords:

Ant Colony Optimization (ACO), Path Relinking, Permutation Flow-Shop Scheduling

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