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[학술저널]

  • 학술저널

Habibeh Nazif(Payame Noor University)

DOI : 10.7232/iems.2019.18.3.360

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초록

In this paper, Job Shop Scheduling Problem (JSSP) with the objective of minimizing the maximum completion time is considered. JSSP is a typical NP-hard problem which has a broad engineering application background. An Effective Ant Colony Optimization (EACO) algorithm utilized a two-stage ant graph is developed to solve the problem. Moreover, the relative mechanisms such as the pheromone updating rule, and the state transition rule that fit for such ant graph is also presented. The proposed EACO algorithm is tested on a set of benchmark instances, and also compared with some other algorithms reported in the literature. The experimental results showed a superior performance of EACO in makespan, which also verifies the effectiveness and efficiency of the proposed method.

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ABSTRACT
1. INTRODUCTION
2. JOB SHOP SCHEDULING PROBLEM
3. EFFECTIVE ANT COLONY OPTIMIZATION ALGORITHM
4. COMPUTATIONAL EXPERIMENTS
5. CONCLUSIONS
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