• 산업경영시스템학회지
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• 제44권2호
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• pp.36-42
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• 2021

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

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

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.359-366
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• 2005

Most engineering optimization are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithm, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search(HS) meta-heuristic algorithm-based approach for structural size optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Two classical space truss optimization problems are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to structural engineering problems than those obtained using current algorithms.

• 한국정보통신학회논문지
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• 제19권5호
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• pp.1084-1090
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• 2015

본 논문에서는 무선 센서 네트워크에서 네트워크의 감시영역을 최대화하기 위해 센서 노드를 효과적으로 배치하는 타부 서치 알고리즘을 제안한다. 무선 센서 네트워크에서 센서 노드의 수가 증가하게 되면 네트워크의 감시영역을 최대화하기 위한 계산량은 급격히 늘어나게 된다. 본 논문에서는 센서 배치 밀도가 높은 네트워크에서 적정한 실행 시간 내에 네트워크의 감시영역을 최대화하는 타부 서치 알고리즘을 제안하며, 효율적인 검색을 위해 타부 서치 알고리즘의 새로운 이웃해 생성 동작을 제안한다. 제안된 알고리즘은 네트워크의 최대 감시영역과 실행속도 관점에서 성능을 평가하며, 평가 결과에서 제안된 알고리즘이 기존의 알고리즘에 비해 성능이 우수함을 보인다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.652-658
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• 1998

We introduce the concept of a bi-population scheme for real-coded GAs consisting of an explorer sub-Ga and an exploiter sub-GA. The explorer sub-GA mainly performs global exploration of the search space, and incorporates a restart mechanism to help avoid being trapped at local optima. The exploiter sub-GA performs exploitation of fit local areas of the search space around the neighborhood of the best-so-far solution. Thus the search function of the algorithm is divided. the proposed technique exhibits performance significantly superior to standard GAs on two complex highly multimodal problems.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.131-135
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• 2008

In this paper, we deal with a hierarchical location-allocation problem in designing the broadband convergence networks (BcN). The objective is to minimize the total cost of switch and cable while satisfying the quality of service (QoS). We formulate the problem as an integer programming model and develop the Tabu Search (TS) heuristic algorithm to find a good feasible solution within a reasonable time limit. Initial solution is obtained by using the tree structure. Three neighborhood generation mechanisms are used by local search heuristic: insertion, switch up, and switch down. In order to demonstrate the effectiveness of the proposed algorithm, we generate lower bounds from nonlinear QoS relaxation problem. We present promising computational results of the proposed solution procedures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.2162-2176
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• 2018

Chemical reactions have an intricate relationship with the search for better-quality neighborhood solutions to optimization problems. A catalytic reaction for chemical reactions provides a clue and a framework to solve complicated optimization problems. The application of a catalytic reaction reveals new information hidden in the optimization problem and provides a non-intuitive perspective. This paper proposes a new simulated catalytic reaction method for search in optimization problems. In the experiments using this method, significantly improved results are obtained in almost all graphs tested by applying to a graph bisection problem, which is a representative problem of combinatorial optimization problems.

• Structural Engineering and Mechanics
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• 제77권6호
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• pp.779-795
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• 2021

In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

• 전자공학회논문지S
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• 제34S권6호
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• pp.30-37
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• 1997

We present an efficient technique, bidirectioanl inertial maximum cost search technique, for th edetection and segmentation of circular shaped objects using the spatial information around the neighborhood of the boundary candidates. This technique searches boundary candidates using local pixdl information such as pixel value and its direction. And then to exclude pseudo-boundary caused by shadows or noises, the local contrast is defined between the clique of the boundary candidates and the cliques of the background. In order to effectively segment circular shaped boundary, the technique also uses the curvature based on trigonometirc function which determines circular shaped boundary segments. Since the proposed technique is applied to the pixel cliques instead of a pixel itself, it is proposed method can easily find out circular boundaries form iamges of the PCB containing circular shaped parts and the trees with round fruits compared to boundary detection by using the pixel information and the laplacian curvature.

• 대한산업공학회지
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• 제33권4호
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• pp.469-479
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• 2007

This paper focuses on the capacitated vehicle routing problem that determines the routes of vehicles in such a way that each customer must be visited exactly once by one vehicle starting and terminating at the depot while the vehicle capacity and the travel time constraints must be satisfied. The objective is to minimize the total traveling cost. Due to the complexity of the problem, we suggest a tabu search algorithm that combines the features of the existing search heuristics. In particular, our algorithm incorporates the neighborhood reduction method using the proximity information of the Voronoi diagram corresponding to each problem instance. To show the performance of the Voronoi tabu search algorithm suggested in this paper, computational experiments are done on the benchmark problems and the test results are reported.