Job Scheduling in Virtual Manufacturing Cells With Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach
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Dosyalar
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper discusses the job scheduling problem in virtual manufacturing cells (VMCs) with the objective of makespan minimization. In the VMC scheduling problem, each job undergoes different processing routes and there is a set of machines to process any operation. Jobs are produced in lot and lot-streaming is permitted. In addition, machines are distributed through the facility, which raises the travelling time issue. For this reason, the decisions are machine assignments, starting times and sub-lot sizes of the operations. We develop a new Mixed Integer Linear Programming (MILP) formulation that considers all aspects of the problem. Owing to the intractability matter, it is unlikely that the MILP could provide solutions for big-sized instances within a reasonable amount of time. We therefore present a Genetic Algorithm (GA) with a new chromosome structure for the VMC environment. Based on a wide range of examinations, comparative results show that GA is quite favourable and that it obtains the optimum solution for any of the instances in the case where sub-lot number equals 1.
Açıklama
Anahtar Kelimeler
scheduling, virtual manufacturing cells (VMCs), flexible job-shop scheduling problem, lot-streaming, integer programming, genetic algorithms
Kaynak
Journal of the Operational Research Society
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
63
Sayı
Künye
Kesen, S. E., Gungor, Z., (2012). Job Scheduling in Virtual Manufacturing Cells With Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach. Journal of the Operational Research Society, (63), 683-695. Doi:10.1057/jors.2011.86
