Multi-Objective Optimization for Job Shop Scheduling Problem Using Genetic Algorithm

Multi-objective optimization is presented in this paper for job shop scheduling problem. Coding is executed using MATLAB for tardiness and makespan. Genetic algorithm is implemented using MATLAB toolbox, and Pareto frontier is used to analyze the results. Benchmark is selected for simulation.

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Bibliographic Details
Published in:ICFAI journal of operations management 2018-02, Vol.17 (1), p.58-63
Main Authors: Kagthara, M S, Bhatt, M G
Format: Article
Language:English
Subjects:
Benchmarks
Combinatorics
Computer simulation
Employment
Genetic algorithms
Industrial engineering
Integer programming
Job shop scheduling
Job shops
Linear programming
Mathematical models
Mathematical programming
Matlab
Multiple objective analysis
Optimization
Optimization algorithms
Optimization techniques
Production planning
Production scheduling
Productivity
Scheduling
Studies
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Description
Summary:Multi-objective optimization is presented in this paper for job shop scheduling problem. Coding is executed using MATLAB for tardiness and makespan. Genetic algorithm is implemented using MATLAB toolbox, and Pareto frontier is used to analyze the results. Benchmark is selected for simulation.
ISSN:0972-6888