Two Hybrid Algorithms for Solving the Multi Objective Batch Scheduling Problem on a Single Machine Based on Simulated Annealing and Clustering Methods

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Author	Hamidreza Haddad, Payam Ghanbari
ISSN	2225-7217
On Pages	38-51
Volume No.	1
Issue No.	1
Issue Date	February 01, 2020
Publishing Date	February 01, 2020
Keywords	Batch scheduling; single machine; deterioration; job values; clustering; release date

Abstract

Single machine batching scheduling is one of the most important problems in the manufacturing area which has applied many applications especially in field of supply chain management. In the real world industry, the manufacturers require a suitable plan so as to deliver the finished items to their customers with minimum delivery and tardiness cost. This paper studies the present problem with objective of minimizing the total tardiness and maximizing the job values on a single machine when the deteriorated jobs are delivered to each customer in various size batches and proposed a mathematical model for this target. Furthermore, all jobs are not ready for process at time zero and each job is ready based on a predefined release date. In order to solve the proposed model, two hybrid algorithms, based on simulated annealing and clustering methods are offered and the results are compared with the global optimums that are generated by Lingo 10 software. Furthermore, based on the effective factors of the problem, a number of sensitivity analyses are also implemented. Computational study demonstrates that using clustering methods leads to specified improvements in batching process.

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