An application of unrelated parallel machine scheduling with sequence-dependent setups at Vestel Electronics

Name: An application of unrelated parallel machine scheduling with sequence-dependent setups at Vestel Electronics
Author: Ekici, Ali, Elyasi, Milad, Özener, Okan Örsan, Sarıkaya, M. B.

İsim	An application of unrelated parallel machine scheduling with sequence-dependent setups at Vestel Electronics
Yazar	Ekici, Ali, Elyasi, Milad, Özener, Okan Örsan, Sarıkaya, M. B.
Basım Tarihi:	2019-11
Basım Yeri	- Elsevier
Konu	Unrelated parallel machines, Sequence-dependent setups, Tabu search, Set partitioning, Matheuristic
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0305-0548
Kayıt Numarası	27df3d3a-38bb-4a4b-a2c7-33fdc0e58e3e
Lokasyon	Industrial Engineering
Tarih	2019-11
Örnek Metin	In this paper, we analyze a variant of the unrelated parallel machine scheduling problem with the objective of minimizing the total tardiness and earliness in the presence of sequence-dependent setups, unequal release times, machine-job compatibility restrictions and workload balance requirements. This study is motivated by the production scheduling operations at a television manufacturer, Vestel Electronics. Vestel produces LCD/LED TVs and has a significant market share in the consumer electronics sector in Europe. TV manufacturing is planned based on a make-to-order strategy, and Vestel uses 15 assembly lines to produce 110 different product groups and 3817 different models. Once the orders are received, production scheduling is performed at the beginning of each month, and the goal is to satisfy the demand on time as much as possible. The decision maker has to consider several factors including job-assembly line compatibility, the release and due dates of the jobs and a workload balance among different assembly lines when forming the production schedule. To address this problem, we propose a wide range of heuristics including (i) a sequential algorithm, (ii) a tabu search algorithm, (iii) a random set partitioning approach, and (iv) a novel matheuristic approach utilizing the local intensification and global diversification powers of a tabu search algorithm. Through a computational study, we observe that all the proposed approaches not only significantly outperform the current practice but also provide solutions with around 5% less optimality gap compared to a benchmark algorithm in the literature.
DOI	10.1016/j.cor.2019.06.007
Cilt	111

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An application of unrelated parallel machine scheduling with sequence-dependent setups at Vestel Electronics

Yazar Ekici, Ali, Elyasi, Milad, Özener, Okan Örsan, Sarıkaya, M. B.

Basım Tarihi 2019-11

Basım Yeri - Elsevier

Konu Unrelated parallel machines, Sequence-dependent setups, Tabu search, Set partitioning, Matheuristic

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0305-0548

Kayıt Numarası 27df3d3a-38bb-4a4b-a2c7-33fdc0e58e3e

Lokasyon Industrial Engineering

Tarih 2019-11

Örnek Metin In this paper, we analyze a variant of the unrelated parallel machine scheduling problem with the objective of minimizing the total tardiness and earliness in the presence of sequence-dependent setups, unequal release times, machine-job compatibility restrictions and workload balance requirements. This study is motivated by the production scheduling operations at a television manufacturer, Vestel Electronics. Vestel produces LCD/LED TVs and has a significant market share in the consumer electronics sector in Europe. TV manufacturing is planned based on a make-to-order strategy, and Vestel uses 15 assembly lines to produce 110 different product groups and 3817 different models. Once the orders are received, production scheduling is performed at the beginning of each month, and the goal is to satisfy the demand on time as much as possible. The decision maker has to consider several factors including job-assembly line compatibility, the release and due dates of the jobs and a workload balance among different assembly lines when forming the production schedule. To address this problem, we propose a wide range of heuristics including (i) a sequential algorithm, (ii) a tabu search algorithm, (iii) a random set partitioning approach, and (iv) a novel matheuristic approach utilizing the local intensification and global diversification powers of a tabu search algorithm. Through a computational study, we observe that all the proposed approaches not only significantly outperform the current practice but also provide solutions with around 5% less optimality gap compared to a benchmark algorithm in the literature.

DOI 10.1016/j.cor.2019.06.007

Cilt 111