A Hybrid Nested Partitions Algorithm Combing with Genetic Algorithm for Job Shop Flexible Resource Scheduling

Wan Ning Ding; Hong Qiang Jiao; Zhuo Yi Chen

doi:10.4028/www.scientific.net/AMR.179-180.920

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 179-180A Hybrid Nested Partitions Algorithm Combing with...

A Hybrid Nested Partitions Algorithm Combing with Genetic Algorithm for Job Shop Flexible Resource Scheduling

Abstract:

In this paper, we formulate the Job Shop Flexible Resource Scheduling (JSFRS) problem, and presents a hybrid nested partitions algorithm combining genetic algorithm in sampling scheme for the JSFRS problem. The major part of this work is a generic partitioning scheme was implemented and the Resource Allocation Procedure was incorporated into the NP method framework. Simulation results support our theoretical results and illustrate that the hybrid nested partitions algorithm work as designed and the performance improvements associated with flexible resource scheduling are substantial.

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Periodical:

Advanced Materials Research (Volumes 179-180)

Pages:

920-924

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.179-180.920

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Online since:

January 2011

Authors:

Wan Ning Ding, Hong Qiang Jiao, Zhuo Yi Chen

Keywords:

Combinatorial Optimization, Job Shop Flexible Resource, Nested Partition Algorithm, Scheduling

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References

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