• 한국경영과학회지
• /
• 제19권2호
• /
• pp.177-198
• /
• 1994

We consider an algorithm for the Crew Scheduling Problem (CSP) based on the Transportation Problem approach. The main flows of the algorithm are arranged in three steps. First we propose a heuristic algorithm of the greedy principle to obtain an initial feasible solution. Secondary we present a method of formulating CSP into a Modified Transportation Problem format. Lastly the procedures of network search to get the optimal solution are presented. This algorithm can be applied to the general GSP and also to most combinatorial problems like the Vehicle Routing Problems. The computational results show that the large size CSP's could be tackled.

• 한국세라믹학회:학술대회논문집
• /
• 한국세라믹학회 2000년도 추계총회,초청강연,특별강연,연구발표회
• /
• pp.57.2-57
• /
• 2000

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
• /
• pp.609-614
• /
• 1989

A collision avoidance algorithm based on a heuristic graph search and subgoals is presented. The joint angle space is quantized into cells. The evaluation function for a heuristic search is defined by the sum of the distance between the links of a manipulator and middle planes among the obstables and the distance between the end-effector and the subgoals on desired trajectory. These subgoals reduce the combinatorial explosion in the search space. This method enables us to avoid a dead-lock in searching. Its effectiveness has been verified by simulation studies.

• 한국응용약물학회:학술대회논문집
• /
• 한국응용약물학회 1998년도 Proceedings of UNESCO-internetwork Cooperative Regional Seminar and Workshop on Bioassay Guided Isolation of Bioactive Substances from Natural Products and Microbial Products
• /
• pp.34-37
• /
• 1998

Combinatorial chemistry is one of the most interested topics in the area of drug discovery. One of the most important points is how to find a lead compound that gives the seed structure for designing of a combinatorial library. Natural products is suitable for searching a new bioactive compound with new structure. We have carried out systematic screening works to find natural products possessing the effects on inter-and intra-cellular signaling. Two hundreds extracts of medical plants and two thousands microbial culture broth samples have been tested for the induction and inhibition of IL-2 or IL-6 production (Fig. 1). ELISA is an efficient method for screenings from such a large number of samples. Now, we apply this method to search prion- binding agents.

• Journal of Communications and Networks
• /
• 제7권4호
• /
• pp.471-477
• /
• 2005

This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

• 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.

• 한국세라믹학회지
• /
• 제42권6호
• /
• pp.391-398
• /
• 2005

It is known that $BaMgAl_{10}O_{17}:Eu^{2+}(BAM)$ phosphors currently used have a serious thermal degradation problem. We screened $SrO-B_2O_3-P_2O_5$ system by a solution combinatorial chemistry technique in an attempt to search for a thermally stable blue phosphor for PDPs. A Quantitative Structure Activity Relationship (QSAR) was also obtained using an artificial neural network trained by the result fiom the combinatorial screening. As a result, we proposed a promising composition range in the $SrO-B_2O_3-P_2O_5$ ternary library. These compositions crystallized into a single major phase, $Sr_6BP_5O_{20}:Eu^{2+}$. The structure of $Sr_6BP_5O_{20}:Eu^{2+}$ was clearly determined by ab initio calculation. The luminescent efficiency of $Sr_6BP_5O_{20}:Eu^{2+}$ was 2.8 times of BAM at Vacuum Ultra Violet (VUV) excitation. The thermal stability was also good but the CIE color chromaticity was slightly poor.

• 한국정보처리학회논문지
• /
• 제4권6호
• /
• pp.1550-1556
• /
• 1997

본 논문에서는 진화 알고리즘에 기반하여 조합 최적화 문제를 해결하고자 한다. 진화 알고리즘은 대규모 문제 공간에서 최적화 문제를 해결하는데 적합한 알고리즘이다. 본 논문의 조합 최적화의 예는 경수로 원자로로부터 나온 폐연료를 중수로에서 재사용하는데 필요한 폐연료의 조합 문제이다. 이와 같은 조합 최적화 문제는 0/1 knapsack 문제와 같이 NP-Comprete 문제에 해당한다. 이러한 문제를 해결하기 위해서는 고전적인 진화 알고리즘의 전략에 기반하여 랜덤 연산자를 이용하여 평가 함수 값이 좋은 방향으로만 탐색을 수행하는 방법, 그리고 벡터 연산자를 이용하여 최적의 해를 보다 빨리 얻을 수 있는 휴리스틱을 사용하는 방법이 있다. 본 논문에서는 중수로 연료 조합 문제 영역의 모든 지식을 벡터화하여 벡터의 연산만으로 가능성 검사, 해를 평가하는 방법을 소개한다. 또한 벡터 휴리스틱이 고전적인 진화 알고리즘에 비해 어느 정도의 성능을 보이는지 비교한다.

• 한국정보시스템학회지:정보시스템연구
• /
• 제25권1호
• /
• pp.159-182
• /
• 2016

Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.

• 대한산업공학회지
• /
• 제23권3호
• /
• pp.451-467
• /
• 1997

Tabu search (TS) is a useful strategy that has been successfully applied to a number of complex combinatorial optimization problems. By guiding the search using flexible memory processes and accepting disimproved solutions at some iterations, TS helps alleviate the risk of being trapped at a local optimum. In this article, we propose TS-based heuristics for solving a class of clustering problems, and compare the relative performances of the TS-based heuristic and the simulated annealing (SA) algorithm. Computational experiments show that the TS-based heuristic with a long-term memory offers a higher possibility of finding a better solution, while the TS-based heuristic without a long-term memory performs better than the others in terms of the combined measure of solution quality and computing effort required.