• Industrial Engineering and Management Systems
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• 제15권1호
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• pp.1-10
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• 2016

This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

• 산업공학
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• 제22권2호
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• pp.116-125
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• 2009

We revisit the assembly block storage location assignment problem (ABSLAP) at a shipyard, in order to compensate for the deficiency in performance verification of the heuristic ABSLAP algorithm developed by the previous study. In this paper, we formulate a mathematical programming model of the ABSLAP, refine elaborately the heuristic ABSLAP algorithm, and show the performance of the developed mathematical programming model and the revised heuristic ABSLAP algorithm. In addition, we explain simulation experiments conducted using the revised heuristic ABSLAP algorithm to investigate the influences of block stockyard layouts and production schedule instability on the block stockyard operations.

• International Journal of Reliability and Applications
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• 제9권1호
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• pp.1-5
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• 2008

A heuristic algorithm for reliability optimization of a distributed network system is developed so that the reliability of a large system can be determined efficiently. This heuristic bases on the determination of maximal reliability set of maximum node capacity, maximal link reliability and maximal node degree.

• 산업경영시스템학회지
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• 제15권25호
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• pp.83-90
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• 1992

This paper aims at the problem that design the network of Rig-star type with the minimum cost, which the Ring is composed of the selected nodes(concentrators) among the several candidate nodes on the network and other nodes(terminals) is connected to the Ring by star subnetwork. Especially, we consider the terminal reliability in network design problem. We develop the heuristic algorithm for network design problem to obtain the near optimal(best) solution for problem. We use an add-heuristic method and 2-exchange method in developing the heuristic algorithm.

• 한국정보통신학회논문지
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• 제14권3호
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• pp.663-668
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• 2010

차량을 타고 이동할 경우 좌회전, 우회전, U턴 등의 방향 전환은 차량의 속력 감소의 주요한 요인이 된다. 즉, 같은 거리를 이동할 경우 방향전환이 잦은 경로보다 직진 구간이 많은 경로가 보다 빨리 목적지에 도착할 수 있다. 이 논문에서는 직진성이 높은 경로를 탐색하기 위해서 방향전환비용을 고려한 턴 휴리스틱과 이률 적용한 경로탐색 알고리즘(TA* 알고리즘)을 제안한다. 또한 TA* 알고리즘의 탐색비용을 개선하기 위해서 일부 구간에서만 턴 휴리스틱을 적용하는 가변적인 턴 휴리스틱(VTA* 알고리즘)을 제안한다.

• 전자공학회논문지B
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• 제32B권1호
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• pp.11-20
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• 1995

A new graph problem is formulated to limit the maximum path length of a general directed graph when a minimal set of vertices together with their incident edges are removed from the graph. An optimal algorithm and a heuristic algorithm are proposed and the proposed heuristic algorithm is shown to be effective through experiments using a collection of graphs obtained from large sequential circuits. The heuristic algorithm is based on a feedback vertex set algorithm based on graph reduction.

• 산업경영시스템학회지
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• 제22권51호
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• pp.21-28
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• 1999

The TSP(Traveling Salesman Problem) is one of the most widely studied problems in combinatorial optimization. The most common interpretation of TSP is finding a shortest Hamiltonian tour of all cities. The objective of this paper proposes a new heuristic algorithm MCH(Multi-Convex hulls Heuristic). MCH is a algorithm for finding good approximate solutions to practical TSP. The MCH algorithm is using the characteristics of the optimal tour. The performance results of MCH algorithm are superior to others algorithms (NNH, CCA) in CPU time.

• 산업경영시스템학회지
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• 제28권4호
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• pp.94-101
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• 2005

This paper presents a data-mining aided heuristic algorithm development. The developed algorithm includes three steps. The steps are a uniform selection, development of feature functions and clustering, and a decision tree making. The developed algorithm is employed in designing an optimal multi-station fixture layout. The objective is to minimize the sensitivity function subject to geometric constraints. Its benefit is presented by a comparison with currently available optimization methods.

• 산업경영시스템학회지
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• 제20권43호
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• pp.287-297
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• 1997

This research is concerned with operation control problem for an automated manufacturing system which consists of two machine centers and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time to be included travel time of AGV. A new heuristic algorithm is proposed and a numerical example illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions than the previous algorithms.

• 대한산업공학회지
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• 제14권1호
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• pp.73-82
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• 1988

This research is concerned with production scheduling for FMS (Flexible Manufacturing System) which consists of machine centers served by cycle conveyor. The objective of the research is to develop and evaluate scheduling procedures to minimize the mean flow time. An optimal algorithm called SCTF (Shortest Circle Time First) is proposed when the conveyor runs at minimum possible speed (CS=1) and a heuristic algorithm called SCTJMF (Shortest Cycle Time and Job Matching Algorithm) is suggested when the conveyor runs at double speed (CS=2). The evaluation of the heuristic algorithm was implemented by comparison with the optimal algorithm for 112 experimentations for CS=1 and random schedule. The results showed that the proposed heuristic algorithm provides better solution that can be regarded noticeable when compared with SCTF algorithm and random scheduling.