NDLI: Modeling and Application for Multiobjective Flow-shop Scheduling Using Hybrid Genetic Algorithms

Content Provider	IEEE Xplore Digital Library
Author	Wu Jing-jing Jiang Wen-xiari
Copyright Year	2007
Description	Author affiliation: Donghua Univ., Shanghai (Wu Jing-jing)
Abstract	Numerous real-world problems relating to flow-shop scheduling are characterized by combinatorially explosive alternatives as well as multiple conflicting objectives and are denoted as multiobjective combinatorial optimization problems. The problem of multiobjective optimization with setup times in flow shop is considered in this study. The objective function of the problem is minimization of the weighted sum of total completion time, makespan, maximum tardiness and maximum earliness. An integer programming model is developed for the problem which belongs to NP-hard class by using the hybrid genetic algorithm (HGA) to move from local optimal solution to near optimal solution for flow-shop scheduling problems. Small size problems and large size problems can be solved by the proposed integer programming model. Computational experiments are performed to illustrate the effectiveness and efficiency of the proposed HGA algorithm.
Starting Page	410
Ending Page	415
File Size	2786746
Page Count	6
File Format	PDF
ISBN	9787560322780
DOI	10.1109/ICMSE.2007.4421882
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	HARBIN INSTITUTE OF TEC
Subject Keyword	Job shop scheduling Optimal scheduling Conference management Linear programming setup times genetic algorithms Genetic algorithms multiobjective optimization Technology management flow-shop scheduling Processor scheduling Engineering management Production Resource management
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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