Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 47, Issue 4, Pages 1015-1037Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207540601158807
Keywords
Multistage supply chain; Lead time; Artificial immune system (AIS)
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In this paper a mathematical model for the batch sequencing problem in a multistage supply chain is developed by taking into account three practically important objectives, viz. minimization of lead time, blocking time and due date violation. Attribute dependent operation time, sequence dependent setup time, different due dates, different lot sizes for batches and variable time losses due to interaction among several stages like waiting, idling, and blocking are also considered in the model. The problem is combinatorial in nature and complete enumeration of all its possibilities is computationally prohibitive. Therefore, a metaheuristic, artificial immune system (AIS) is employed to find an optimal/near optimal solution. In order to test the efficacy of AIS in solving the problem, its implementation on four different problems has been studied. Further, the comparative analysis of the results obtained by implementing AIS, genetic algorithm (GA) and simulated annealing (SA) on the proposed model reveals that AIS outperforms GA and SA in solving the underlying problem.
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