• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.781-783
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• 1997

Genetic Algorithm is a kind of an evolution programming based on natural evolution principle. It applied to probabilistic searching, machine learning and optimization, and many good results were reported. Generator maintenance scheduling is an optimization Problem with constraints. This paper applied a genetic algorithm to generator maintenance scheduling problem and tested on sample systems. The results are compared with heuristic method and branch-and-bound method.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.97-103
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• 2016

This paper deals with the cycle time minimization problem that determines the productivity in printed circuit board (PCB) with n components using the m placement machines. This is known as production cycle time determination problem (PCTDP). The polynomial time algorithm to be obtain the optimal solution has been unknown yet, therefore this hard problem classified by NP-complete. This paper gets the initial assignment result with the machine has minimum unit placement time per each component firstly. Then, the balancing process with reallocation from overhead machine to underhead machine. Finally, we perform the swap optimization and get the optimal solution of cycle time $T^*$ within O(mn) computational complexity. For experimental data, the proposed algorithm can be obtain the same result as integer programming+branch-and-bound (IP+B&B) and B&B.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.55-71
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• 2006

We perform a computational study on 0-1 knapsack problems generated under explicit correlation induction. A total of 2000 100-variable test problems are solved. We use two solution methods: (1) a well known heuristic and (2) a representative branch and bound type algorithm. Two different performance measures are considered: (1) the number of nodes needed to find an optimal solution and (2) the relative error of the heuristic solution. We also examine the effect of different joint probability mass functions (pmfs) for the coefficient values on the performance of the solution procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.23-30
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• 2003

This study develops an efficient heuristic which is based on genetic approach for AGVs flow path layout problem. The suggested solution approach uses a algorithm to replace two 0-1 integer programming models and a branch-and-bound search algorithm. Genetic algorithms are a class of heuristic and optimization techniques that imitate the natural selection and evolutionary process. The solution is to determine the flow direction of line in network AGVs. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. Genetic algorithm procedure is suggested, and a simple illustrative example is shown to explain the procedure.

• Proceedings of the IEEK Conference
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• summer
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• pp.400-404
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• 2004

There are many methods to find solutions for Integer Programming problems (IPs) such as the Branch-Bound philosophy or the Cutting Plane algorithm. However, most of them have a problem that is the explosion of sets in the computing process. In addition, GA is known as a heuristic search algorithm for solutions of optimization problems. It is started from a random initial guess solution and attempting to find one that is the best under some criteria and conditions. The paper will study an artificial intelligent method to solve IPs by using Genetic Algorithms (GAs). The original solution of this was presented in the papers of Fabricio Olivetti de Francaand and Kimmo Nieminen [2003]. However, both have several limitations which causes could be operations in GAs. The paper proposes a method to upgrade these operations and computational results are also shown to support these upgrades.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.11a
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• pp.409-416
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• 2004

동적 공급사슬망은 복잡하고 다양한 이해관계를 가진 기업들로 구성되어 있다. 다수의 구매자로부터 주문 의뢰가 동시다발적으로 발생하므로 하위 구성원들은 경쟁적 관계에 놓이게 된다. 그러므로 최적의 공급사슬구성을 위해서는 수평적 경쟁 관계를 고려하여 구성주체들간의 협력관계를 통해 이를 해결하여야 한다. 지금까지의 스케줄링 문제에서는 상위의 구성원이 하위 구성원들을 일방적으로 선택하는 의사결정이 이루어졌으나 본 문제에서는 구성원간의 협력관계에서 에이전트를 통한 다자간 협상을 통해 공급사슬 전체의 최적화를 구성하는 방법론을 제시한다. 본 협상방법론은 단일기계에서 상이한 납기일, 조기생산(earliness), 지연생산(tardiness)을 동시에 고려하였으며 전체 공급사슬의 평균절대편차(Mean Absolute Deviation)의 최소화를 목적으로 하고 있다. 본 협상방법론의 효과성을 증명하기 위해 분지한계법(Branch & Bound)과 비교하고, 알고리즘 구현을 통해 구매자 협상방법론의 최적화 여부를 실험을 통해 증명하였다.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.12a
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• pp.143-154
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• 2005

공급사슬의 구성문제는 주문의 동적환경를 고려하여 전체 관점에서 스케줄링되어야 한다. 이러한 공급사슬구성문제를 본 연구에서는 에이전트 협상 방법론을 통해 해결하고자 한다. 에이전트 협상은 공급사슬망을 경쟁적 관계로 이해하고 개별목적을 가진 구성원 에이전트간의 협상과정을 통해 재스케줄링이 발생되어 공급사슬을 구성하게된다. 지금까지의 연구는 공급사슬 상에서 수직적 통합(vertical integration)을 중심으로 조직의 유연적 조정에 초점이 맞추어졌다. 그러나 본문제에서는 다수의 구매자, 제조자. 공급자간의 3 단계 과정에서 협력적 관계를 통해 개별적 이익을 최대화하면서 공급사슬 전체의 관점에서도 비용 최적화를 이룰 수 있는 다자간 협상방법론을 제안한다. 본 협상방법론의 최적화 여부와 효율성을 Branch & Bound 알고리즘과 비교하여 검증하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.287-295
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• 2004

컨테이너 터미널의 적하 작업은 사전에 계획된 순서대로 컨테이너를 장치장(yard)에서 하나씩 반출하여 선박에 선적하는 작업이다. 만일 현재 반출하고자 하는 컨테이너의 상단에 다른 컨테이너들이 장치되어 있다면, 부득이하게 위에 놓여 있는 컨테이너들을 다른 곳으로 옮겨야 하는 재취급(rehandling)이 발생하고 이로 인하여 반출 작업은 지연된다. 본 논문에서는 적하 계획이 수립되어 장치장의 한 베이(bay)내 컨테이너들의 반출 순서가 결정되었을 때, 반출 시작 시점까지 남는 유휴 시간을 활용하여 재취급이 발생하지 않도록 컨테이너들을 재정돈(이적, 리마샬링)하는 방안을 제안한다. 본 제안 방안은 분지 한계법(branch and bound)을 적용하여 컨테이너 이동 계획을 탐색하며, 생성된 해는 최소의 컨테이너 이동 횟수가 보장된다. 4 단 6 열과 5 단 9 열의 장치장 구조를 대상으로 실험한 결과 99% 이상의 상황에서 허용할 수 있는 시간 내에 계획을 수립할 수 있음을 확인하였다.

• Journal of the military operations research society of Korea
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• v.23 no.1
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• pp.14-24
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• 1997

This study is to develop an optimal surveillance units assignment model in order to obtain the maximized surveillance efficiency with the limited surveillance units. There are many mathematical models which deal with problems to assign weapons such as aircrafts, missiles and guns to targets. These models minimize the lost required to attack, the threat forecast from the enemy, or both of them. However, a problem of the efficient assignment of surveillance units is not studied yet, nevertbless it is important in the battlefield surveillance system. This paper is concerned with the development of the optimal surveillance units assignment model using integer programming. An optimal integer solution of the model can be obtained by using linear programming and branch and bound method.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.288-292
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• 1987

The purpose of this paper is to develope the parallel computation algorithm that enables it to minimize the completion tine of computation execution of the entire subtasks, under the constraints of the series-parallel precedence relation in each subtask. The developed algorithm was applied to the control of a robot manipulator functioned by multi-CPU's and to obtain the minimum time schedule so that real time control may be achieved. The completion time of computation execution was minimized by applying "Variable" Branch and Bound algorithm which was developed In this paper in determining the optimum ordered schedule for each CPU.