Job Scheduling in Virtual Manufacturing Cells With Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach

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Tarih

2012

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