• Title/Summary/Keyword: heuristic method

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A Hybrid Heuristic Approach for Supply Chain Planningwith n Multi-Level Multi-Item Capacitated Lot Sizing Model (자원제약하의 다단계 다품목 공급사슬망 생산계획을 위한 휴리스틱 알고리즘)

  • Shin Hyun-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.1
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    • pp.89-95
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    • 2006
  • Planning distributed manufacturing logistics is one of main issues in supply chain management. This paper proposes a hybrid heuristic approach for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network. MLCLSP corresponds to a mixed integer programming (MIP) problem. With integer variable solutions determined by heuristic search, this MIP problem becomes linear program (LP). By repeatedly solving the relaxed MIP problems with a heuristic search method in a hybrid manner, this proposed approach allocates finite manufacturing resources fur each distributed facilities and generates feasible production plans. Meta heuristic search algorithm is presented to solve the MIP problems. The experimental test evaluates the computational performance under a variety of problem scenarios.

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A study on shortest problem between specified nodes with multiple travel time (다수개의 여행시간이 주어진 경우의 지정된 마디간의 최단경로 문제)

  • 이명석;박순달
    • Korean Management Science Review
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    • v.7 no.2
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    • pp.51-57
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    • 1990
  • The purpose of this thesis is to find the shortest path between two nodes on an acyclic network where the arc costs are determined by the starting time at the starting node of the arc. A branch and bound method for optimal solutions and a heuristic method is developed. In heuristic method Dijkstra algorithm is modified to maintain the minimum arrival times of maximum informations in the each time period at each node and is updated by the result with the insertion technique. Expermetal results among two methods are presented with regard to run time and solution qualities.

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Study on a Layout Design Method for Leisure Ship Production Factories using a Heuristic Location-Allocation Algorithm

  • Lee, Dong-Kun;Jeong, Yong-Kuk;Shin, Jong-Gye
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.19 no.3
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    • pp.277-284
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    • 2013
  • To ensure that the production system of a factory is efficient, the factory layout design should consider the location and material flow plans of facilities, workshops, and storage areas. Highly productive factories need to have an optimized layout planning process, and a customized design methodology of the production system is a necessity for feasible layout planning. This paper presents a method for designing a layout module's size and shape and provides a heuristic location-allocation algorithm for the modules. The method is implemented and validated using a rich internet application-based platform. The layout design method is based on the leisure ship production process; this method can be used for designing the layout of a new factory or remodeling an existing factory and its production system. In contrast to existing layout methods, the inputs required for the proposed method, such as target products, production processes, and human-resource plans, are simple. This layout design method provides a useful solution for the initial stage of factory design.

The Bisection Seed Detection Heuristic for Solving the Capacitated Vehicle Routing Problem (한정 용량 차량 경로 탐색 문제에서 이분 시드 검출 법에 의한 발견적 해법)

  • Ko, Jun-Taek;Yu, Young-Hoon;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.15 no.1
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    • pp.1-14
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    • 2009
  • The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.

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A Heuristic Algorithm for Crew Scheduling Problems (발견적 승무계획 해법의 연구)

  • 김정식
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.9 no.13
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    • pp.79-86
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    • 1986
  • This paper presents a heuristic algorithm for a crew scheduling problem with dead head flights. This paper modifies and improves saving method for finding the Multiple Salesman tours in the graph. The results show that the computing time from this algorithm is implemented very much than those from general crew scheduling algorithms by set covering models.

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A Heuristic Algorithm for The Vehicle Routing and Scheduling Problem (차량경로일정문제의 발견적 해법)

  • 김기태;도승용;성명기;박순달
    • Journal of the military operations research society of Korea
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    • v.26 no.1
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    • pp.89-99
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    • 2000
  • This paper deals with a heuristic algorithm for the vehicle routing-scheduling problem to minimize the total travel distance and the total cost. Because the aim of the Clarke-Wright method, one of famous heuristic methods, is to minimize the total travel distance of vehicles, it cannot consider the cost if the cost and the travel distance is not proportional. In the Clarke-Wright method, the route of each vehicle is found by using the saving matrix which is made by an assumption that the vehicle comes back to the starting point. The problem dealt with in the paper, however, does not need the vehicle to come back because each vehicle has its hoping-start-points and hoping-destination-points. Therefore we need a different saving matrix appropriate to this occasion. We propose a method to find an initial solution by applying network simplex method after transforming the vehicle routing-scheduling problem into the minimum cost problem. Moreover, we propose a method to minimize the total travel distance by using the modified saving matrix which is appropriate to no-return occasion and the method for the case of plural types of vehicles and freights.

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A Heuristic for the Design of Distributed Computing Systems (발견적 해법을 이용한 분산 컴퓨터 시스템 설계)

  • 손승현;김재련
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.40
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    • pp.169-178
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    • 1996
  • Geographically dispersed computing system is made of computers interconnected by a telecommunications network. To make the system operated efficiently, system designer must determine the allocation of data files to each node. In designing such distributed computing system, the most important issue is the determination of the numbers and the locations where database files are allocated. This is commonly referred to as the file allocation problem (FAP)[3]. The proposed model is a 0/l integer programming problem minimizing the sum of file storage costs and communication(query and update) costs. File allocation problem belongs to the class of NP-Complete problems. Because of the complexity, it is hard to solve. So, this paper presents an efficient heuristic algorithm to solve the file allocation problem using Tabu Search Technique. By comparing the optimal solutions with the heuristic solutions, it is believed that the proposed heuristic algorithm gives good solutions. Through the experimentation of various starting points and tabu restrictions, this paper presents fast and efficient method to solve the file allocation problem in the distributed computing system.

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Nesting Expert System using Heuristic Search (휴리스틱 탐색 기법을 이용한 네스팅 전문가 시스템)

  • Sheen, Dong-Mok
    • Journal of Ocean Engineering and Technology
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    • v.26 no.4
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    • pp.8-14
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    • 2012
  • Two dimensional nesting is a common problem in industries such as the shipbuilding, automotive, clothing, shoe-making, and furniture industries, in which various parts are cut off from stock or packed in a flat space while minimizing waste or unoccupied space. Nesting is known as an NP-complete problem, which has a solution time proportional to the superpolynomial of the input size. It becomes practically impossible to find an optimal solution using algorithmic methods as the number of shapes to nest increases. Therefore, heuristic methods are commonly used to solve nesting problems. This paper presents an expert system that uses a heuristic search method based on an evaluation function for nesting problems, in which parts and stock are represented by pixels. The system is developed in CLIPS, an expert system shell, and is applied to four different kinds of example problems to verify its applicability in practical problems.

Heuristic Process Capability Indices Using Distribution-decomposition Methods (분포분할법을 이용한 휴리스틱 공정능력지수의 비교 분석)

  • Chang, Youngsoon
    • Journal of Korean Society for Quality Management
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    • v.41 no.2
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    • pp.233-248
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    • 2013
  • Purpose: This study develops heuristic process capability indices (PCIs) using distribution-decomposition methods and evaluates the performances. The heuristic methods decompose the variation of a quality characteristic into upper and lower deviations and adjust the value of the PCIs using decomposed deviations in accordance with the skewness. The weighted variance(WV), new WV(NWV), scaled WV(SWV), and weighted standard deviation(WSD) methods are considered. Methods: The performances of the heuristic PCIs are investigated under the varied situations such as various skewed distributions, sample sizes, and specifications. Results: WV PCI is the best under the normal populations, WSD and SWV PCIs are the best under the low skewed populations, NWV PCI is the best under the moderate and high skewed populations. Conclusion: Comprehensive analysis shows that the NWV method is most adequate for a practical use.