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Title: Novel genetic algorithm for short-term scheduling of sequence dependent changeovers in multiproduct polymer plants
Authors: Ramteke, M.
Srinivasan, R. 
Keywords: Grades
Linear programming
Multi-objective optimization
Real-coded genetic algorithm
Stochastic modeling
Issue Date: 14-Dec-2011
Citation: Ramteke, M., Srinivasan, R. (2011-12-14). Novel genetic algorithm for short-term scheduling of sequence dependent changeovers in multiproduct polymer plants. Computers and Chemical Engineering 35 (12) : 2945-2959. ScholarBank@NUS Repository.
Abstract: Polymer plants generally operate to produce different grades of product from the same reactor. Such systems commonly require short-term scheduling to meet market demand. One important requirement in continuous-time scheduling of such systems is to satisfy a variety of constraints, including identifying feasible sequences of the predecessor and successor jobs to effectively handle changeovers. In this study, a new genetic algorithm (GA) is proposed to solve such job sequencing problems. The proposed GA uses real-coded chromosome to represent job orders and their sequences in the schedule. The novelty is that the representation ensures that all constraints are satisfied a priori, except the sequence constraint which is handled by penalizing violations. Three important problems relevant to polymer industry are solved to obtain optimal schedules. The first deals with the sequencing constraint between individual product orders, the second with sequencing constraint between groups of product orders, while the third incorporates batching with scheduling. © 2011 Elsevier Ltd.
Source Title: Computers and Chemical Engineering
ISSN: 00981354
Appears in Collections:Staff Publications

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