• 한국항공우주학회지
• /
• 제37권8호
• /
• pp.737-743
• /
• 2009

본 연구는 Tabu Search를 이용하여 LHP의 최적설계를 진행하는 방법과 절차 및 결과를 제시하고자 한다. 최적설계의 목적은 항공기에 탑재된 리튬이온 전지의 작동온도 조건을 만족하면서 LHP의 중량을 최소화시키는 것이다. 전지는 고에너지 밀도의 특성으로 항공기에 장착된 고에너지 레이저의 동력원으로 사용되는 것으로 가정되었다. 해석은 Steady state analysis model에 기초하였으며 메타모델로 근사화하였다. 최적화 결과로 Tabu Search는 유전알고리듬 등 다른 비 구배기반 최적화 방법에 비해 비교적 적은 계산 시간을 소요하면서도 전역해를 보장하였으나 난수에 의해 초기해를 바꾸어 가면서 최적화를 여러 번 시도해야 하는 단점이 있었다. 그리고 최적화 과정을 통해 기 발표된 LHP와 동일한 성능을 가지면서도 경량화된 LHP를 얻을 수 있었다.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
• /
• pp.135-138
• /
• 1996

In solving the Travel Salesman Problem(TSP), we easily reach local optimal solutions with the existing methods such as TWO-OPT, THREE-OPT, and Lin-Kernighen. Tabu search, as a meta heuristic, is a good mechanism to get an optimal or a near optimal solution escaping from the local optimal. By utilizing AI concepts, tabu search continues to search for improved solutions. In this study, we focus on developing a new neighborhood structure that maintains the feasibility of the tours created by exchange operations in TSP. Intelligent methods are discussed, which keeps feasible tour routes even after exchanging several edges continuously. An extended tabu search model, performing cycle detection and diversification with memory structure, is applied to TSP. The model uses effectively the information gathered during the search process. Finally, the results of tabu search and simulated annealing are compared based on the TSP problems in the prior literatures.

• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 2008년도 추계학술대회
• /
• pp.35-39
• /
• 2008

This paper considers the sequencing of products in mixed model assembly lines. The sequence which minimizes overall utility work in car assembly lines reduce the cycle time, the number of utility workers, and the risk of conveyor stopping. The sequencing problem is solved using Tabu Search. Tabu Search is a heuristic method which can provide a near optimal solution in real time. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1994년도 추계학술발표회 발표논문집; 연세대학교경영관, 서울; 8 Oct. 1994
• /
• pp.224-231
• /
• 1994

• 경영과학
• /
• 제13권1호
• /
• pp.13-27
• /
• 1996

This paper considers the sequencing problem in mixed model assembly lines with hybrid workstation types and sequence-dependent setup times. Computation time is often a critical factor in choosing a method of determining the sequence. We develop a mathematical formulation of the problem to minimize the overall length of a line, and present a tabu search technique which can provide a near optimal solution in real time. The proposed technique is compared with a genetic algorithm and a branch-and-bound method. Experimental results are reported to demonstrate the efficiency of the technique.

• Journal of Advanced Marine Engineering and Technology
• /
• 제38권2호
• /
• pp.225-232
• /
• 2014

The traditional RAP (Redundancy Allocation Problem) of complex systems has considered only the redundancy of subsystem with homogeneous components. In this paper we extend it as a RAP of complex systems with heterogeneous components which is more flexible than the case of homogeneous components. We model this problem as a nonlinear integer programming problem, find its optimal solution by tabu search, and suggest an example of the efficient reliability design with heterogeneous components. In order to improve the quality of the solution of the tabu search, we suggest a modified tabu search to employ an adaptive procedure (1-opt or 2-opt exchange) to generate the efficient neighborhood solutions. Computational results show that our modified procedure obtains better solutions as the size of problem increases from 30 to 50, even though it requires rather more computing time. With some adjustment of the parameters of the proposed method, it can be applied to the optimal reliability designs of complex systems of ships.

• Journal of Advanced Marine Engineering and Technology
• /
• 제40권2호
• /
• pp.138-145
• /
• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Management Science and Financial Engineering
• /
• 제10권2호
• /
• pp.89-102
• /
• 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.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2010년도 하계학술대회 논문집
• /
• pp.51-52
• /
• 2010

In order to simplify the offline identification of induction motor parameters, a method based on optimization using a Tabu Search algorithm is proposed. The Tabu Search algorithm is used to minimize the error between the actual data and an estimated model. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.

• 산업경영시스템학회지
• /
• 제25권2호
• /
• pp.92-101
• /
• 2002

The Job Shop Scheduling Problem(JSSP) is concerned with schedule of m different machines and n jobs where each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. The purpose of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the large scale job shop scheduling. The proposed heuristic method is based on a Tabu Search(TS) and on a Constraint Satisfaction Technique(CST). In this paper, ILOG libraries is used to embody the job shop model, and a CST is developed for this model to generate the increased solution. Then, TS is employed to overcome the increased search time of CST on the increased problem size md to refine the next-current solution. Also, this paper presents the new way of finding neighbourhood solution using TS. On applying TS, a new way of finding neighbourhood solution is presented. Computational experiments on well known sets of MT and LA problem instances show that, in several cases, our approach yields better results than the other heuristic procedures discussed In literature.