Multiobjective Artificial Immune Algorithm for Flexible Job Shop Scheduling Problem

Zohreh Davarzani; Mohammad-R Akbarzadeh-T; Nima Khairdoost

Multiobjective Artificial Immune Algorithm for Flexible Job Shop Scheduling Problem

원문정보

Zohreh Davarzani, Mohammad-R Akbarzadeh-T, Nima Khairdoost

보안공학연구지원센터(IJHIT) International Journal of Hybrid Information Technology Vol.5 No.3 2012.07 pp.75-88

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초록

영어

Flexible Job shop scheduling is very important in production management and combinatorial optimization. It is NP-hard problem and consists of two sub-problems: sequencing and assignment. Multiobjective Flexible Job-Shop Scheduling Problems (MFJSSP) is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. In this paper a Multiobjective Artificial Immune Algorithm (MAIA) for FJSSP is presented. The proposed algorithm increases the speed of convergence and diversity of population. Kacem and Bradimart data are used to evaluate the effectiveness of MAIA. The experimental results show a better performance in comparison to other approaches.

Abstract
1. Introduction
2. Definition of Flexible job-shop Scheduling Problem
3. Multiobjective Optimization Problem
4. Artificial Immune Algorithm
5. Proposed Algorithm
  5.1. Antibody Representation
  5.2. Non Dominated Sorting
  5.3. Mutation Operator
  5.4. Diversification Operator
6. Experimental Setup and Simulation
7. Conclusion
Reference

키워드

저자정보

Zohreh Davarzani Department of Computer Engineering, Beyhagh Institute of Higher Education
Mohammad-R Akbarzadeh-T Department of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad
Nima Khairdoost Department of Computer Engineering, Faculty of Engineering, University of Isfahan

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자료제공 : 네이버학술정보

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