• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.642-647
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• 2014

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.159-164
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• 2004

Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots and then scheduling these sublots in order to accelerate the completion of jobs in a multi-stage production system. Anew genetic algorithm (NGA) is proposed for an-job, m-machine, equal-size sublot lot-streaming flow shop scheduling problem with delivery windows in which the objective is to minimize the mean weighted absolute deviation of job completion times from due dates. The performance of NGA is compared with that of an adjacent pairwise interchange (API) method and the results of computational experiments show that NGA works well for this type of problem.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.213-220
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• 2007

This paper considers a two-stage hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. Each job is processed through the two production stages in stages, each of which has multiple identical parallel machines. The problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also suggested to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.69-100
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• 2009

In this paper, we consider a relatively new two-machine flow shop scheduling problem where the unit time WIP cost increases as a job passes through various stages in the production process, and the objective is to minimize the total WIP (work-in-process) cost. Specifically, we study three special cases of the problem. First, we consider the problem where processing times on machine 1 are identical. Second, the problem with identical processing times on machine 2 is examined. The recognition version of the both problems is unary NP-complete (or NP-complete in strong sense). For each problem, we suggest two simple and intuitive heuristics and find the worst case bound on relative error. Third, we consider the problem where the processing time of a job on each machine is proportional to a base processing time. For this problem, we show that a known heuristic finds an optimal schedule.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.299-303
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• 2004

In the Internet, to guarantee transmission rate and delay and to achieve fair bandwidth allocation, many per-flow scheduling algorithms, such as fair queueing, which have many desirable properties for congestion control, have been proposed and designed. However, algorithms based on per-flow need maintain rate state, buffer management and packet scheduling, so that it cost great deal ： implement. Therefore, in this paper, to implement routers cost-effectively, we propose CS-FNE algorithm based on FNE in Core-Stateless network We evaluate CS-FNE comparing with four additional algorithms i.e., CSFQ, FRED, RED and DRR, in several different, configurations and traffic sources. Through simulation results, we show that CS-FNE algorithm can allocate fair bandwidth approximately and is simpler and easier to implement than other per-flow basis queueing mechanisms.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.206-214
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• 2016

This paper deals with the no-wait flow shop scheduling problem in order to minimize the total time to complete the schedule or makespan. It is introduced a constructive heuristic which builds the production schedule from job partial sequences by using an appropriate mechanism of insertion. An extensive computational experiment has been performed to evaluate the performance of proposed heuristic. Experimental results have clearly shown that the presented heuristic provides better solutions than those from the best heuristics existing.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.325-328
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• 2003

Fierce competition in today's global markets, the heightened expectation of customers have forced business enterprises to invest in, and focus attentions on, their Supply Chains, Also Cross Docking is an essential part of SC, and integrating Cross Docking with vehicle routing scheduling is needed to smoothly link the physical flow of SC, However, there is no the mathematical model which focuses on Cross Docking with vehicle routing scheduling. Therefore, the integrating model considers Cross Docking and vehicle routing scheduling will be developed in this paper. And the solution based on Tabu algorithm to this model will be provided.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• IE interfaces
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• v.22 no.1
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• pp.63-72
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• 2009

This paper considers a transporter scheduling problem under dynamic block transportation environment in shipbuilding. In dynamic situations, there exist the addition, cancellation or change of block transportation requirements, sudden breakdowns and maintenance of transporters. The transportation of the blocks in the shipyard has some distinct characteristics. Some blocks are available to be picked up at a specific time during the planning horizon while some other blocks need to be delivered before a specific time. These requirements cause two penalty times: 1) delay times incurred when a block is picked up after a required start time, and 2) tardy times incurred when a block shipment is completed after the required delivery time. The blocks are located at different areas in the shipyard and transported by transporters. The objective of this paper is to propose a heuristic algorithm based on a network flow model which minimize the weighted sum of empty transporter travel times, delay times, and tardy times. Also, a rolling-horizon scheduling method is proposed for dynamic block transportation environment. The performance of the proposed heuristic algorithms are evaluated through a simulation experiment.