JOURNAL ARTICLE

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

Wan Ning DingHong Qiang JiaoZhuo Yi Chen

Year: 2011 Journal:   Advanced materials research Vol: 179-180 Pages: 920-924   Publisher: Trans Tech Publications

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.

Keywords:
Combing Computer science Scheduling (production processes) Genetic algorithm Scheme (mathematics) Algorithm Job shop scheduling Mathematical optimization Flow shop scheduling Distributed computing Mathematics Machine learning Schedule Materials science

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Topics

Scheduling and Optimization Algorithms
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Optimization and Search Problems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Manufacturing and Logistics Optimization
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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