• 전자공학회논문지A
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• 제32A권2호
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• pp.111-119
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• 1995

In this paper, we propose an efficient SA(simulated annealing) algorithm for the synthesis of binary phase computer generated hologram. SA algorithm is a method to find the optimal solution through iterative technique. It is important that selecting cost function and parameters within this algorithm. The aplications of converentional SA algorithm to synthesize parameters within this algorithm. The applications of conventional SA algorithm to synthesize binary hologram have many problems because of inappropriate paramters and cost function. So, we propose a new cost function and a calculation technique of proper parameters required to achieve the optimal solution. Computer simulation results show that the proposed method is better than conventional method in terms of diffraction efficiency and reconstruction error. Also, we show the reconstructed images by the proposed method through optical esperiment.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.7-14
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• 2011

In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.

• 한국경영과학회지
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• 제22권4호
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• pp.51-69
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• 1997

Recently Lee et al[5] developed an approximation algorithm for the performance evaluation of the open queueing networks with blocking. This algorithm, which solves the exponential queueing networks with general configuration is developed based on the symmetrical decomposition approach and is reported to have many advantages over the previous algorithmsf. In addition to being very accurate, this algorithm is reported to be quite simple, pretty fast and solves very general configurations. In this study, we show that if a network has a tree-like configurations, the algorithm developed by Lee at al, always converges to the unique solution. To prove the theoretical results pertaining to the algorithm, some properties associated with symmetrical decomposition approach are exploited. The results obtained in this study such as the proofs of convergence of the algorithm as well as uniquences of the solution would contribute to the theoretical study for the non-tandem configurating of open queueing network.

• 대한안전경영과학회지
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• 제10권3호
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• pp.253-265
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• 2008

In this paper, we developed a heuristic algorithm to assign job to workers in parallel line inspection process without sequence. Objective of assigning job in inspection process is only to assign job to workers evenly. But this objective needs much time and effort since there are many cases in assigning job and cases increase geometrically if the number of job and worker increases. In order to solve this problem, we proposed heuristic algorithm to assign job to workers evenly. Experiments of assigning job are performed to evaluate performance of this heuristic algorithm. The result shows that heuristic algorithm can find the optimal solution to assign job to workers evenly in many type of cases. Especially, in case there are more than two optimal solutions, this heuristic algorithm can find the optimal solution with 98% accuracy.

• 대한안전경영과학회지
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• 제11권3호
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• pp.157-166
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• 2009

In this study, we developed a heuristic algorithm to get better efficiency of clustering than conventional algorithms. Conventional clustering algorithm had lower efficiency of clustering as there were no solid method for selecting initial center of cluster and as they had difficulty in search solution for clustering. EMC(Expanded Moving Center) heuristic algorithm was suggested to clear the problem of low efficiency in clustering. We developed algorithm to select initial center of cluster and search solution systematically in clustering. Experiments of clustering are performed to evaluate performance of EMC heuristic algorithm. Squared-error of EMC heuristic algorithm showed better performance for real case study and improved greatly with increase of cluster number than the other ones.

• 한국CDE학회논문집
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• 제15권1호
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• pp.24-32
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• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

• 한국군사과학기술학회지
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• 제13권1호
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• pp.1-8
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• 2010

This paper presents global and optimal solution for weapon assignment problems using the Munkres assignment algorithm. We propose a new modeling method of weapon assignment problems concerning some constraints of weapon systems. In this paper, we compares the Munkres weapon assignment algorithm with two other algorithms employing a search tree model in terms of computational complexity and performance. One is an optimal algorithm using exhausted search and the other is a greedy algorithm which selects the first search result as a solution. The experiment results show that the Munkres weapon assignment algorithm has better performance and less computational complexity in comparison with the two other algorithms.

• 대한산업공학회지
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• 제19권4호
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• pp.13-22
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• 1993

The aircraft scheduling, which is used to determine flight frequency, departure times and aircraft type assignments, is main problem of airline's planning. This paper proposes a new algorithm for aircraft scheduling that is to maximize airline profits. This paper proposes a column generation algorithm to get an optimal solution of the continous relaxation not using all the feasible variables, but using only a limited number of variables that is generated whenever it is necessary. Using this algorithm, proposes an optimal algorithm to get an optimal integer solution of aircraft scheduling problem efficiently. The effectiveness of the column generation algorithm and the optimal algorithm is illustrated by the computational results obtained from a series of real airline problems.

• 대한교통학회지
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• 제18권6호
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• pp.89-99
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• 2000

전통적인 OD조사에 의한 OD추정방법의 여러 문제점들로 인해 링크에서 관측된 교통량과 기존OD를 결합해 새로운 OD를 추정하고자 하는 연구들이 지속되고 있으며, 그 필요성도 증대되고 있다. 그러한 기법중의 하나가 Yang(1995)이 제시한 바이레벨 모형으로, 그는 일반화최소자승법을 풀기위한 Sensitivity Analysis Based (SAB)을 제시하였다. 그러나 SAB 알고리즘은 두가지 중요한 문제점을 가지고 있다. 첫 번째 문제는 실제 OD를 알기가 어렵기 때문에, 기존 OD 조사시의 통행패턴이 현재의 통행패턴과 큰 변화가 없다는 가정 하에, 기존 OD를 추정시 중요한 추정기준으로 설정한다는 점이다. 그러나 이러한 기존 OD에 대한 추정의 종속성으로 인해, SAB는 기존 OD와 실제 OD의 차이가 큰 경우 정확한 해를 도출하지 못하고 추정결과가 일관적(robust)이지 않게 도출된다. 두 번째 문제는 SAB는 통행패턴 추정시 선형근사화를 가정하기 때문에 게임이론적 측면에서 전제로 설정한 완전한 Stackelberg 상황을 구현하지 못한다는 점이다. 이러한 문제점을 피하기 위해서는 기존 OD의 오차나 관측교통량의 오차에 대해 일관적이고 안정적인 해도출 기법이 필요하다. 본 연구의 목적은 SAB를 비롯한 기존 바이레벨 OD추정기법의 문제점을 지적하고 이에 대한 대안기법을 제시하는 것이다. OD추정의 문제는 본질적으로 비선형이고 비볼록하기 때문에, 다중해를 도출하게 된다. 따라서 전역해 탐색기법이 필요한데, 본 연구에서는 전역최적화가 가능한 유전알고리즘(Genetic Algorithm)을 이용한 OD추정모형(GA-Model:GAM)을 제시하였다. 사례네트워크에 대한 비교분석결과, GAM은 기존 OD의 오타에 대해 크게 종속적이지 않으며 OD구조가 변하는 경우에도 추정이 가능하여, 일반적으로 실제 OD를 알 수 없는 (기존OD의 오차가 어느 정도인지를 알 수 없는) 도시부 네트워크에서 신뢰성있는 추정력을 보였다.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.130-139
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• 2002

In this paper, at first, we investigate existing algorithms for finding the minimum infinity-norm solution of consistent linear equations and then propose a new algorithm. The proposed algorithm is intended to includes the advantages of computational efficiency as well as geometric explicitness. As a practical application example, optimum trajectory planning for redundant robot manipulators is considered. Also, an efficient approach avoiding discontinuity in trajectory is proposed by resolving the non-uniqueness problem of minimum infinity-norm solution. To be specific, the proposed method for checking possible discontinuity does not need any other algorithms in checking the possibility of discontinuity while previous work needs specially designed checking courses. To show the usefulness of the proposed techniques, an example calculating minimum infinity-norm solution for comparing the computational efficiency as well as the trajectory planning for a redundant robot manipulator are included.