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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2928
Title: Genetic algorithm for large-size multi-stage batch plant scheduling
Authors: He, Yaohua
Hui, David Chi Wai
Keywords: Multi-stage scheduling
Mixed-integer linear programming
Genetic algorithm
Heuristic rule
Active schedule
Issue Date: Mar-2007
Citation: Chemical engineering science, v. 62, no. 5, March 2007, p. 1504-1523
Abstract: This paper presents a heuristic approach based on genetic algorithm (GA) for solving large-size multi-stage multi-product scheduling problem (MMSP) in batch plant. The proposed approach is suitable for different scheduling objectives, such as total process time, total flow time, etc. In the algorithm, solutions to the problem are represented by chromosomes that will be evolved by GA. A chromosome consists of order sequences corresponding to the processing stages. These order sequences are then assigned to processing units according to assignment strategies such as forward or backward assignment, active scheduling technique or similar measures, and some heuristic rules. All these measures greatly reduce unnecessary search space and increase the search speed. In addition, a penalty method for handling the constraints in the problem, e.g., the forbidden changeovers, is adopted, which avoids the infeasibility during the GA search and further greatly increases the search speed.
Rights: Chemical engineering science © 2007 Elsevier. The Journal's web site is located at http://www.sciencedirect.com/
URI: http://hdl.handle.net/1783.1/2928
Appears in Collections:CBME Journal/Magazine Articles

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