Lot streaming in a two-machine mixed shop

Çetinkaya, Ferda Can; Duman, Mehmet

doi:10.1007/s00170-009-2473-1

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…Besides the studies mentioned above, lot streaming studies for other two-and three-machine manufacturing shops are scarce. There are studies considering open shops (Şen & Benli, 1999), hybrid flow shops (Kim et al, 1997;Zhang et al, 2003;Zhang et al, 2005;Liu, 2008;Defersha, 2011;Defersha & Chen, 2012a;Naderi & Yazdani, 2015;Cheng et al, 2016;Zhang et al, 2017;Wang et al, 2019;Li et al, 2020), and mixed shops (Çetinkaya & Duman, 2010), job shops (Buscher & Shen, 2009;Defersha & Chen, 2012b), and assembly shops (Sarin et al, 2011;Yao & Sarin, 2014;Nejati et al, 2016;Cheng & Sarin, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling with lot streaming in a two-machine re-entrant flow shop

Çetinkaya

Duman²

2021

Oper. Res. Eng. Sci. Theor. Appl.

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Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time.

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Section: Literature Reviewmentioning

confidence: 99%

Scheduling with lot streaming in a two-machine re-entrant flow shop

Çetinkaya

Duman²

2021

Oper. Res. Eng. Sci. Theor. Appl.

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“…Splitting an entire lot into sub lots to be moved to a downstream machine allows overlapping of different operations on the same product while the work needs to be completed on the upstream machine. Cetinkaya and Duman 1 addressed the lot streaming problem of multiple jobs in a two-machine mixed shop; their objective was to reach C max . Liu 2 developed an effective heuristic method for discrete lot streaming with variable sub-lots.…”

Section: Literature Reviewmentioning

confidence: 99%

A new critical path method and a memetic algorithm for flexible job shop scheduling with overlapping operations

2012

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The flexible job shop scheduling problem (FJSP) is an extension of the classical job shop scheduling problem (JSP) which allows an operation to be processed by any machine from a given set of machines. FJSP is NP-hard and presents two major difficulties. The first is to assign each operation to a machine out of a set of capable machines; and the second deals with sequencing the assigned operations on the machines. However, it is quite difficult to obtain an optimal solution to this problem in medium and large size problems with traditional optimization approaches. In this paper, a memetic algorithm (MA) for flexible job shop scheduling with overlapping operations is proposed that solves the FJSP to minimize makespan. We also proposed a heuristic that uses the critical path method (CPM) in order to improve the results of MA and reduce the objective function. The experimental results of MA and CPM show that our approach is capable of achieving the optimal solution for small size problems and near-optimal solutions for medium and large size problems in a reasonable time.

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A new genetic algorithm for lot-streaming flow shop scheduling with limited capacity buffers

Ventura

Yoon

2012

J Intell Manuf

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Lot streaming in a two-machine mixed shop

Cited by 4 publications

References 28 publications

Scheduling with lot streaming in a two-machine re-entrant flow shop

Scheduling with lot streaming in a two-machine re-entrant flow shop

A new critical path method and a memetic algorithm for flexible job shop scheduling with overlapping operations

A new genetic algorithm for lot-streaming flow shop scheduling with limited capacity buffers

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