• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.22-31
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• 2015

In this paper, a two-stage hybrid flow shop problem is considered. Specifically, there exist identical parallel machines at stage 1 and two dedicated machines at stage 2, and the objective of the problem is to minimize makespan. After being processed by any machine at stage 1, a job must be processed by a specific machine at stage 2 depending on the job type, and one type of jobs can have different processing times on each machine. First, we introduce the problem and establish complexity of several variations of the problem. For some special cases, we develop optimal polynomial time solution procedures. Then, we establish some simple lower bounds for the problem. In order to solve this NP-hard problem, three heuristics based on simple rules such as the Johnson's rule and the LPT (Longest Processing Time first) rule are developed. For each of the heuristics, we provide some theoretical analysis and find some worst case bound on relative error. Finally, we empirically evaluate the heuristics.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.254-265
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• 1999

We consider two stage hybrid flowshop scheduling problem when there are two non-identical parallel machines at the first stage, and only one machine at the second stage. Several well-known sequence-first allocate-second heuristics are considered first. We then propose an allocate-first sequence-second heuristic to find minimum makespan schedule. The effectiveness of the proposed heuristic algorithm in finding a minimum makespan schedule is empirically evaluated by comparing with easily computable lower bound. The proposed heuristic algorithm as well as the existing heuristics are evaluated by simulation in four cases which have different processing time distribution, and it is found that the proposed algorithm is more effective in every case.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.57-73
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• 1985

Group scheduling problem in a multi-stage manufacturing system is reviewed and two heuristic procedures for minimizing the makespan are developed by employing the methods of flow shop sequencing heuristics with a slight modification. The comparisons among the five heuristics, three previously reported heuristics and two heuristics suggested by this study, are made on different problem sizes. The computational results indicate that NEH-GS method gives better group schedules than the other heuristics tested, but its computation time increases rapidly as the problem size increases. On the other hand, CDS-GS method provides relatively good group schedules with less computation time compared with NEH-GS method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3236-3245
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• 1994

The nesting of two-dimensional patterns onto a given raw sheet has applications in a number industries. It is a common problem often faced by designers in the shipbuilding, garment making, blanking die design, glass and wood industries. This paper presents a multi-stage layout approach for nesting two-dimensional patterns by using artificial intelligence techniques with a relatively short computation time. The raw material with irregular boundaries and internal defects which must be considered in various cases of nesting was also investigated in this study. The proposed nesting approach consists of two stages : initial layout stage and layout improvement stage. The initial layout configuration is achieved by the self-organizing assisted layout(SOAL) algorithm while in the layout improvement stage, the simulated annealing(SA) is adopted for a finer optimization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.307-309
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• 1996

This paper analyses a deterministic scheduling problem concerned with manufacturing two types of components at a pre-assembly stage which consists of two independent feeding machines each producing its own type of component. Each type represents a unique component which may have variations in its size or quality. Therefore, the completion time of each component depends on both its type and quality (size) variations. Such manufactured components are subsequently assembled into various component dependent products. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs(products) where the completion time of each job is measured by the latest completion time of its two components at the pre-assembly stage. The problem is shown to be NP-complete in the strong sense. A WSPT rule coupled with a machine-aggregation idea is developed for good heuristics which show the error bound of 2.

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.95-112
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• 2006

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts and/or components over a planning horizon. The case of assembly product structure is considered while the resource capacity constraints are explicitly considered. A cost-based objective is considered that minimizes the sum of disassembly operation and inventory holding costs. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To test the performance of the heuristic, computational experiments are done on randomly generated problems, and the results show that the heuristic gives near optimal solutions within a very short amount of computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.63-71
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• 2003

This paper analyses a deterministic scheduling problem concerned with manufacturing multiple types of components at a pre-assembly stage composed of parallel fabrication machines. Each component part is machined on a fabrication machine specified in advance. The manufactured components are subsequently assembled into products. The completion time of a job(product) is measured by the latest completion time of its all components at the pre-assembly stage. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs. Two lower bounds are derived and tested in a branch-and-bound scheme. Also, three constructive heuristic algorithms are developed based on the machine aggregation and greedy strategies. Some empirical evaluation of the performance of the proposed branch-and-bound and heuristic algorithms are also performed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.77-86
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• 2012

We consider the capacitated lot-sizing and scheduling problem for a paper remanufacturing system that produces several types of corrugated cardboards. The problem is to determine the lot sizes as well as the sequence of lots for the objective of minimizing the sum of setup and inventory holding costs while satisfying the demand and the machine capacity over a given planning horizon. In particular, the paper remanufacturing system has sequence-dependent setup costs that depend on the type of product just completed and on the product to be processed. Also, the setup state at one period can be carried over to the next period. An integer programming model is presented to describe the problem. Due to the complexity of the problem, we modify the existing two-stage heuristics in which an initial solution is obtained and then it is improved using a multi-pass interchange method. To show the performances of the heuristics, computational experiments were done using the real data, and a significant amount of improvement is reported.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.2
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• pp.45-56
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• 2012

This paper considers a supply chain consisting of a component manufacturer and a product manufacturer. The component manufacturer provides components for the product manufacturer based on a vendor-managed inventory type of supply contract, and also faces demands from the market with the option of to accept or reject each incoming demand. Using the Markov decision process model, we examine the structure of the optimal production control and inventory rationing policy. Two types of heuristics are presented. One is the fixed-buffer policy and the other uses two linear functions. We implement a computational study and present managerial insights based on the observations.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.35-47
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• 2006

This paper considers an integrated scheduling problem for consecutive production and delivery stages in a two-stage supply chain. The Production is performed on a single facility and then the finished products are delivered to the customer by capacitated multiple vehicles. The objective of this paper is to obtain job sequencing and delivery batching minimizing the total cost of the associated WIP inventory, finished product inventory and delivery. The inventory cost is characterized by the sum of weighted flowtime. The delivery cost is proportional to the required number of delivery batches. Some polynomial-solvable cases are derived. For the general case, two efficient heuristic algorithms are suggested, and then the heuristics are tested through some numerical experiments.