Journal Published Online: 24 March 2017
Volume 1, Issue 1

Demand Response in Flow Shop With Job Due Dates Using Genetic Algorithm Approach

CODEN: SSMSCY

Abstract

Demand side management (DSM) has shown great potential in reducing the operating cost for energy intensive manufacturing industries. In this paper, we considered a permutation flow shop with process flexibility enabling the jobs to be processed at different speeds with a trade-off between the processing time and the power consumption. We formulated a multi-objective scheduling problem with two objectives: minimizing total earliness/tardiness cost and minimizing total energy consumption. We used an improved non-dominated sorting genetic algorithm and tested its performance with different randomly generated instances. We also investigated a mathematical programming approach for comparative analysis. The computational experiments confirmed that our proposed genetic algorithm approach was scalable and performed well in obtaining near-optimal solutions in a reasonable time.

Author Information

Nayak, A.
School of Industrial Engineering, Purdue Univ., West Lafayette, IN, US
Fang, K.
College of Management and Economics, Tianjin Univ., Tianjin Shi, CN
Lee, S.
School of Industrial Engineering, Purdue Univ., West Lafayette, IN, US
Pages: 21
Price: Free
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Details
Stock #: SSMS20160006
ISSN: 2520-6478
DOI: 10.1520/SSMS20160006