Minimizing the Makespan in the 3-Machine Assembly-Type Flowshop Scheduling Problem

Lee, Chung‐Yee; Cheng, T.C.E.; Lin, Bertrand M.T.

doi:10.1287/mnsc.39.5.616

Cited by 265 publications

(121 citation statements)

References 17 publications

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“…The special case where all the jobs have the same processing time on the second-stage machine is polynomially solvable for both the problem (Cheng and Wang, 1998) and the max || 3 C MAF problem (Lee et al, 1993). In this section we shall show that the special case of the later problem…”

Section: Np-hardnessmentioning

confidence: 92%

“…In the past decades, this seminal work has inspired numerous research endeavors in the scheduling literature (Pinedo 2001, Reisman et al 1997. As a generalization of Johnson's two-machine flowshop, the three-machine assembly flowshop problem motivated by the manufacturing of fire engines was studied by Lee et al (1993). Like the three-machine flowshop problem (Garey et al 1979), the problem to minimize the makespan in an assembly flowshop becomes computationally intractable.…”

Section: Introductionmentioning

confidence: 99%

“…anticipatory machine-dependent setup times. Theoretically, the problem we study in this paper concerns a combination of the models presented by Lee et al (1993) and Cheng and Wang (1998).…”

Section: Introductionmentioning

confidence: 99%

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Scheduling in an assembly-type production chain with batch transfer

Lin

Cheng

Chou

2007

Omega

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This paper addresses a three-machine assembly-type flowshop scheduling problem, which frequently arises from manufacturing process management as well as from supply chain management. Machines one and two are arranged in parallel for producing component parts individually, and machine three is an assembly line arranged as the second-stage of a flowshop for processing the component parts in batches. Whenever a batch is formed on the second-stage machine, a constant setup time is required. The objective is to minimize the makespan. In this study we establish the strong NP-hardness of the problem for the case where all the jobs have the same processing time on the second-stage machine. We then explore a useful property, based upon which a special case can be optimally solved in polynomial time. We also study several heuristic algorithms to generate quality approximate solutions for the general problem. Computational experiments are conducted to evaluate the effectiveness of the algorithms.

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Section: Np-hardnessmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Scheduling in an assembly-type production chain with batch transfer

Lin

Cheng

Chou

2007

Omega

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“…(Pinedo, 2012). When the objective function is the makespan, the problem has been proved to be strongly NP-complete for three or more machines (Lee, Cheng, & Lin, 1993) and for the tardiness objective (Du et al, 2012). A generalization of the FS and parallel-machines environments is the FFS.…”

Section: Introductionmentioning

confidence: 99%

Flow-shop scheduling problem under uncertainties: Review and trends

González-Neira¹,

Montoya‐Torres²,

Barrera³

2017

10.5267/j.ijiec

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Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

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“…For multiple jobs (with each job consisting of one unit of a product), the assembly scheduling problem was first studied by Lee et al, (1993); for the objective of minimising the makespan. Potts et al (1995) have shown that this problem is strongly NP-hard, and have provided a polynomial-time approximation algorithm with a worst-case performance bound.…”

Section: Introductionmentioning

confidence: 99%

Single-batch lot streaming in a two-stage assembly system

Sarin

Yao

Trietsch

2011

IJPS

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Abstract:We address a single-batch lot streaming problem for a two-stage assembly system. The first stage consists of m parallel subassembly machines, each devoted to a component type. A single assembly machine at the second stage assembles a unit of a product after all m components (one each from the subassembly machines) are ready. The batch consists of U units. Detached or attached setups are necessary before the start of the first item on each machine. Given a fixed maximal number of sublots, the problem is to determine integer sublot sizes to minimise the makespan. We present a polynomial-time algorithm to obtain an optimal solution Keywords: scheduling; lot streaming; two-stage assembly system; makespan; setup; line of balance.Reference to this paper should be made as follows: Sarin, S.C., Yao, L. and Dan, T. (2011) 'Single-batch lot streaming in a two-stage assembly system', Int. J. Planning and Scheduling, Vol. 1, Nos. 1/2, pp.90-108.Biographical notes: Subhash C. Sarin is Paul T. Norton Endowed Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech. His areas of research and teaching interests are in production scheduling, applied mathematical programming, and design and analysis of manufacturing systems. He has published several papers in Industrial Engineering and Operations Research journals, has co-authored two books in the production scheduling area, and has served on the editorial boards of many journals. He is recipient of several prestigious awards at the university, state and national levels. Dan Trietsch, PhD (Summa Cum Laude, Tel Aviv University), MBA (Cum Laude, Tel Aviv University), BSME (Technion) is a professor of industrial engineering at American University of Armenia. He has authored and co-authored research and books on optimal network design (generalised Euclidean Steiner Trees), highway and highway network design, project purchasing under stochastic lead times, lot splitting, scheduling hub airports, statistical quality control, and stochastic scheduling subject to optimal service level. His recent co-authored work presents and validates PERT 21, a simple but powerful stochastic scheduling engine for PERT, featuring the Parkinson distribution with a lognormal core and history-based parameters.

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Minimizing the Makespan in the 3-Machine Assembly-Type Flowshop Scheduling Problem

Cited by 265 publications

References 17 publications

Scheduling in an assembly-type production chain with batch transfer

Scheduling in an assembly-type production chain with batch transfer

Flow-shop scheduling problem under uncertainties: Review and trends

Single-batch lot streaming in a two-stage assembly system

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