• Title/Summary/Keyword: Heuristic search

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Development of Reliability-Based Optimum Design of High-Speed Railway Bridges Considering Structure-Rail Longitudinal Interaction and Structure-Vehicle Interaction Using Heuristic Decision Method (Heuristic Decision Method를 이용하여 구조물-궤도 종방향 상호작용 및 구조물-차량 상호작용을 고려한 고속철도 교량의 신뢰성 최적설계 기법 개발)

  • Ihm, Yeong-Rok
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.3
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    • pp.31-38
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    • 2010
  • In this study, it is suggested that it has to reliability-based design methodology with respect to bridge structure-rail longitudinal interaction and bridge structure-vehicle interaction. For the structural analysis, commercial package, ABAQUS, are used for a three-dimensional finite element analysis. The optimization process utilizes a well-known optimizer, ADS(Automated Design Synthesis). Optimization technique is utilized the ALM-BFGS method for global area search and Golden Section Method for 1-D search. In general, ALM-BFGS method don't need the 1-D search, and that algorithm converge a 0.1~0.2 of Push-Off factor. But in this study, value of Push-Off factor is used 90, therefore 1-D search should be needed for effective convergency. That algorithm contains the "heuristic decision method". As a result of optimum design of 2-main steel girder birdge with 5${\times}$(1@50m), design methodology suggested in this study was demonstrated more economic and efficient than existing design and LCC optimization not considering bridge-rail longitudinal interaction and bridge-vehicle interaction.

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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Heuristic Algorithms for Optimization of Energy Consumption in Wireless Access Networks

  • Lorincz, Josip;Capone, Antonio;Begusic, Dinko
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.626-648
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    • 2011
  • Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

Heuristic Approach for Lot Sizing and Scheduling Problem with State Dependent Setup Time

  • Han, Jung-Hee
    • Industrial Engineering and Management Systems
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    • v.10 no.1
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    • pp.74-83
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    • 2011
  • In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

Meta-Heuristic Algorithms for a Multi-Product Dynamic Lot-Sizing Problem with a Freight Container Cost

  • Kim, Byung-Soo;Lee, Woon-Seek
    • Industrial Engineering and Management Systems
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    • v.11 no.3
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    • pp.288-298
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    • 2012
  • Lot sizing and shipment scheduling are two interrelated decisions made by a manufacturing plant and a third-party logistics distribution center. This paper analyzes a dynamic inbound ordering problem and shipment problem with a freight container cost, in which the order size of multiple products and single container type are simultaneously considered. In the problem, each ordered product placed in a period is immediately shipped by some freight containers in the period, and the total freight cost is proportional to the number of containers employed. It is assumed that the load size of each product is equal and backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the shipment schedule that minimize the total costs, which consist of production cost, inventory holding cost, and freight cost. Because the problem is NP-hard, we propose three meta-heuristic algorithms: a simulated annealing algorithm, a genetic algorithm, and a new population-based evolutionary meta-heuristic called self-evolution algorithm. The performance of the meta-heuristic algorithms is compared with a local search heuristic proposed by the previous paper in terms of the average deviation from the optimal solution in small size problems and the average deviation from the best one among the replications of the meta-heuristic algorithms in large size problems.

Tabu Search for Job Shop Scheduling (Job Shop 일정계획을 위한 Tabu Search)

  • Kim, Yeo-Keun;Bae, Sang-Yun;Lee, Deog-Seong
    • Journal of Korean Institute of Industrial Engineers
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    • v.21 no.3
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    • pp.409-428
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    • 1995
  • Job shop scheduling with m different machines and n different jobs is a NP-hard problem of combinatorial optimization. The purpose of the paper is to develop the heuristic method using tabu search for job shop scheduling to minimize makespan or mean flowtime. To apply tabu search to job shop scheduling problem, in this paper we propose the several move methods that employ insert moves in order to generate the neighbor solutions, and present the efficient rescheduling procedure that yields active schedule for a changed operation sequence by a move of operations. We also discuss the tabu search techniques of diversifying the search of solution space as well as the simple tabu search. By experiments, we find the appropriate tabu list size and tabu attributes, and analyze the proposed tabu search techniques with respect to the quality of solutions and the efforts of computation. The experimental results show that the proposed tabu search techniques using long-term memory function have the ability to search a good solution, and are more efficient in the mean flowtime minimization problem than in the makespan minimization.

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Optimal Cutting Plan for 1D Parts Using Genetic Algorithm and Heuristics (유전자알고리즘 및 경험법칙을 이용한 1차원 부재의 최적 절단계획)

  • Cho, K.H.
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.554-558
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    • 2001
  • In this study, a hybrid method is used to search the pseudo-optimal solution for the I-dimentional nesting problem. This method is composed of the genetic algorithm for the global search and a simple heuristic one for the local search near the pseudo optimal solution. Several simulation results show that the hybrid method gives very satisfactory results.

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A Processor Assignment Problem for ATM Switch Configuration

  • Han, Junghee;Lee, YoungHo
    • Management Science and Financial Engineering
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    • v.10 no.2
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    • pp.89-102
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    • 2004
  • In this paper, we deal with a processor assignment problem that minimizes the total traffic load of an ATM switch controller by optimally assigning processors to ATM interface units. We develop an integer programming (IP) model for the problem, and devise an effective tabu search heuristic. Computational results reveal the efficacy of the proposed tabu search procedure, finding a good quality solution within 5% of optimality gap.

Application of tree search to a control problem

  • Miyashita, Mitsutaka;Inooka, Hikaru
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.896-900
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    • 1988
  • Tree search can be applied to a control problem if the system is a discrete-time one and if the control input takes only discrete values. This paper considers the application of heuristic tree search to a simple control problem. The results of simulation studies show the good possibility of this approach to a control problem.

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Cost Relaxation Method to Escape from a Local Optimum of the Traveling Salesman Problem (외판원문제에서 국지해를 탈출하기 위한 비용완화법)

  • Kwon, Sang-Ho;Kim, Sung-Min;Kang, Maing-Kyu
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.2
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    • pp.120-129
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    • 2004
  • This paper provides a simple but effective method, cost relaxation to escape from a local optimum of the traveling salesman problem. We would find a better solution if we repeat a local search heuristic at a different initial solution. To find a different initial solution, we use the cost relaxation method relaxing the cost of arcs. We used the Lin-Kernighan algorithm as a local search heuristic. In experimental result, we tested large instances, 30 random instances and 34 real world instances. In real-world instances, we found average 0.17% better above the optimum solution than the Concorde known as the chained Lin-Kernighan. In clustered random instances, we found average 0.9% better above the optimum solution than the Concorde.