• 한국산학기술학회논문지
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• 제3권1호
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• pp.10-19
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• 2002

본고는 다종, 소규모 회분식 공정 또는 공장을 수학적 프로그래밍 기법으로 최적 설계하는 방법에 대한 것이다. 제안된 일반 회분식 공장문제는 Papageorgaki와 Reklaitis에 의해 혼합정수비선형식(MINLP)으로 수립된 것인데, 최적해답을 보장하며 공장의 확장 등 불확실성을 고려하여 선형화 한 후(MILP) 푸는 방법론이 제시되었다. Bende식 문제분할 방식을 개조하여 몇가지 예제에 대한 풀이를 제시하였다. IBM의 OSL 최적화 패키지를 이용하였고 MILP를 직접 푸는 경우보다 계산시간을 크게 단축할 수 있었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.170-174
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• 2003

In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.

• 대한산업공학회지
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• 제16권2호
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• pp.109-117
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• 1990

In this paper we study a mathematical programming model for the single-card KANBAN system in a multi-stage capacitated general-type-structure production. Until now this production type setting has not been studied. The modeling of this problem results in a complex integer programming which can be modified to the more simple integer programming model. We present a heuristic method and some numerical examples. Though the presented method doesn't always find an optimal solution, this method guarantees to find a feasible solution. We expect this work to be practised in the real fields.

• 한국컴퓨터정보학회논문지
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• 제7권3호
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• pp.42-48
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• 2002

배치(Placement)는 VLSI 회로의 physical design에서 중요한 단계로서 회로의 성능을 최대로 하기 위하여 회로 모듈의 집합을 배치시키는 문제이며, 배치 문제에서 최적의 해를 얻기 위해 클러스터 성장(cluster growth), 시뮬레이티드 어닐링(simulated annealing; SA), ILP(integer linear programming)등의 방식이 이용된다. 본 논문에서는 배치 문제에 대하여 유전자 알고리즘(genetic algorithm; GA)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링 방식과 비교, 분석하였다.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.235-245
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• 2018

This study first analyzes the necessity and the validity of procuring nuclear-powered submarines, and presents an optimization model as an integer program to determine a minimum required level of them. For an optimization model, we characterize a submarine's mission, ability and availability, and apply these to the model by constraints. Then, we assign the submarines available currently and the nuclear-powered submarines, that will be newly introduced, to the predefined missions over the planning time periods in a way that the number of nuclear-powered submarines be minimized. Randomly generated missions are employed to solve a mission assignment problem, and the results show that our integer programming model provides an optimal solution as designed, and this can provide a guideline for other weapon system procurement processes.

• 한국경영과학회지
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• 제41권3호
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• pp.23-36
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• 2016

We consider a model that minimizes the total cost incurred by assigning available weapons to existing targets in order to reduce enemy threats, which is called the weapon target assignment problem (WTAP). This study addresses the stochastic versions of WTAP, in which data, such as the probability of destroying a target, are given randomly (i.e., data are identified with certain probability distributions). For each type of random data or parameter, we provide a stochastic optimization model on the basis of the expected value or scenario enumeration. In particular, when the probabilities of destroying targets depending on weapons are stochastic, we present a stochastic programming formulation with a simple recourse. We show that the stochastic model can be transformed into a deterministic equivalent mixed integer programming model under a certain discrete probability distribution of randomness. We solve the stochastic model to obtain an optimal solution via the mixed integer programming model and compare this solution with that of the deterministic model.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.305-308
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• 2007

In this paper we suggest an efficient evolutionary approach based on topological sort techniques for precedence constrained TSPs. The determination of optimal sequence has much to offer to downstream project management and opens up new opportunities for supply chains and logistics. Experimental results show that the suggested approach is a good alternative to locate optimal solution for complicated precedence constrained sequencing as in optimization method for instance.

• 한국경영과학회지
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• 제23권2호
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• pp.83-101
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• 1998

Assembly U-lines are increasingly accepted in industry, especially just-in-time production systems, for the efficient utilization of workforce. In this paper, we present an integer programming formulation and a branch-and-bound method for balancing the U-line with the objective of minimizing the number of workstations with a fixed cycle time. In the mathematical model, we provide the method that can reduce the number of variables and constraints. The proposed branch-and-bound method searches the optimal solution based on a depth-first-search. To efficiently search for the optimal solutions to the problems, an assignment rule is used in the method. Bounding strategies and dominance rules are also utilized. Some problems require a large amount of computation time to find the optimal solutions. For this reason. some heuristic fathoming rules are also proposed. Extensive experiments with test-bed problems in the literature are carried out to show the performance of the proposed method. The computational results show that our method is promising in solution quality.

• 전기학회논문지
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• 제56권10호
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• pp.1721-1730
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• 2007

SThis paper proposes a new dispatch scheduling algorithm in interconnected regional system operations. The dispatch scheduling formulated as mixed integer non-linear programming (MINLP) problem can efficiently be computed by generalized Benders decomposition (GBD) algorithm. GBD guarantees adequate computation speed and solution convergency since it decomposes a primal problem into a master problem and subproblems for simplicity. In addition, the inter-temporal optimal power flow (OPF) subproblem of the dispatch scheduling problem is comprised of various variables and constraints considering time-continuity and it makes the inter-temporal OPF complex due to increased dimensions of the optimization problem. In this paper, regional decomposition technique based on auxiliary problem principle (APP) algorithm is introduced to obtain efficient inter-temporal OPF solution through the parallel implementation. In addition, it can find the most economic dispatch schedule incorporating power transaction without private information open. Therefore, it can be expanded as an efficient dispatch scheduling model for interconnected system operation.

• 산업경영시스템학회지
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• 제33권2호
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• pp.1-8
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• 2010

A vendor selection problem consists of two different kinds of decision making. First one is to choose the best suppliers among all possible suppliers and the next is to allocate the optimal quantities of orders among the selected vendors. In this study, an integration of the technique for order preference by similarity to ideal solution (TOPSIS) and a multi-objective mixed integer programming (MOMIP) is developed to account for all qualitative and quantitative factors which are used to evaluate and choose the best group of vendors and to decide the optimal order quantity for each vendor. A solution methodology for the vendor selection model of multiple-vendor, multiple-item with multiple decision criteria and in respect to finite vendor capacity is presented.