Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ces.2010.05.032
Title: A binary coding genetic algorithm for multi-purpose process scheduling: A case study
Authors: He, Y. 
Hui, C.-W.
Keywords: Binary coding
Genetic algorithm
Multi-purpose batch plant
Process systems engineering
Scheduling
Special crossover
Issue Date: Aug-2010
Citation: He, Y., Hui, C.-W. (2010-08). A binary coding genetic algorithm for multi-purpose process scheduling: A case study. Chemical Engineering Science 65 (16) : 4816-4828. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ces.2010.05.032
Abstract: This paper presents a novel genetic algorithm (GA) for the scheduling of a typical multi-purpose batch plant with a network structure. Multi-purpose process scheduling is more difficult to deal with compared to single-stage or multi-stage process scheduling. A large amount of literature on this problem has been published and nearly all of the authors used mathematical programming (MP) methods for solution. In the MP methods, a huge number of binary variables, as well as numerous constraints to consider mass balance and sequencing of batches in space/time dimensions, are needed for the large-size problem, which leads to very long computational time. In the proposed GA, only a small part of the binary variables are selected to code into binary chromosomes, which is realized through the identification of crucial products/tasks/units. Due to the logical heuristics utilized to decode a chromosome into a schedule, only the feasible solution space is searched. Our genetic algorithm has first been devised with particular crossover for makespan minimization and then adjusted for production maximization. © 2010 Elsevier Ltd.
Source Title: Chemical Engineering Science
URI: http://scholarbank.nus.edu.sg/handle/10635/112984
ISSN: 00092509
DOI: 10.1016/j.ces.2010.05.032
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