• 한국방재학회 논문집
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• 제10권3호
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• pp.31-38
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• 2010

본 연구에서는 교량 구조물-궤도 종방향 상호작용, 교량 구조물-차량 상호작용을 고려한 신뢰성 최적설계 방법을 제안하고, 알고리즘의 개발을 통하여 본 연구에서 제안한 방법의 효율성을 검증하였다. 구조해석 프로그램은 ABAQUS를 사용하였으며, 최적화 방법은 Automated Design Synthesis(ADS)에서 신뢰성면에서 우수한 ALM-BFGS방법을 사용하였다. 일반적으로 ALM-BFGS방법은 최적해 방향을 탐색하는데 있어 1방향 탐색을 하지 않으며 Push-Off Factor 값이 보통 0.1~0.2에서 대부분 수렴하나 본 연구에서는 'Heuristic Decision Method' 의하여 결정된 Push-Off Factor 값이 90일 때 1방향 탐색인 Golden Section Method의 적용이 필요하였으며, 알고리즘이 잘 수렴함을 확인하였다. 구조물-궤도 종방향 상호작용, 구조물-차량의 상호작용에 의한 응답을 제약조건으로 설정하여 단면 설계시 반영될 수 있도록 하였다. 본 연구는 구조물-궤도 종방향 상호작용 및 구조물-차량 상호작용을 고려한 설계기법에 대한 효율성 및 경제성을 증명하기 위하여 5${\times}$(1@50m) 2주형 강합성 거더교에 대한 최적설계를 수행하였으며, 본 연구에서 제안하는 상호작용을 고려하는 설계기법이 기존의 상호작용을 고려하지 않은 설계방법보다 경제적이며 효율적임을 확인하였다.

• 산업경영시스템학회지
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• 제19권40호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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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.

• Industrial Engineering and Management Systems
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• 제10권1호
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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.

• Industrial Engineering and Management Systems
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• 제11권3호
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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.

• 대한산업공학회지
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• 제21권3호
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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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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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.

• Management Science and Financial Engineering
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• 제10권2호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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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.

• 대한산업공학회지
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• 제30권2호
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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.