• 한국시뮬레이션학회논문지
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• 제14권2호
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• pp.25-34
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• 2005

Determination of component mounting sequence on printed circuit board assembly process is a typical NP-hard problem. It is a kind of traveling salesman problems, but it has one more hard to meet constraint of matching component type per mounting position as well as searching the shortest path. An efficient method is developed by separation of crowed area and allowing up to two slots per component type. A simulation model is constructed using Visual C++ for evaluation of the suggested heuristic.

• 한국경영과학회지
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• 제26권4호
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• pp.133-141
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• 2001

Rapid development in computer and network technology these days has created in environment in which decisions for manufacturing companies can be made in a much broader perspective. Especially, better decisions on production and distribution planning(PDP) problems can be made laking advantage of real time information from all the parties concerned. However, since the PDP problem-a core part of the supply chain management- is known to be the so-called NP-hard problem, so heuristic methods are dominantly used to find out solutions in a reasonable time. As one of those heuristic techniques, many previous studios considered genetic a1gorithms. A standard genetic a1gorithm applies rules of reproduction, gene crossover, and mutation to the pseudo-organisms so the organisms can pass along beneficial and survival-enhancing trails to a new generation. When it comes to representing a chromosome on the problem, it is hard to guarantee an evolution of solutions through classic a1gorithm operations alone, for there exists a strong epitasis among genes. To resolve this problem, we propose a hybrid genetic a1gorithm based on Silver-Meal heuristic. Using IMS-TB(Intelligent Manufacturing System Test-bed) problem sets. the good performance of the proposed a1gorithm is demonstrated.

• 산업경영시스템학회지
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• 제20권41호
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• pp.231-242
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• 1997

This paper describe an approximation method for solving the minimum makespan problem of job shop scheduling with fuzzy processing time. We consider the multi-part production scheduling problem in a job shop scheduling. The job shop scheduling problem is a complex system and a NP-hard problem. The problem is more complex if the processing time is imprecision. The Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Lee-Li fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study propose heuristic algorithm solving the job shop scheduling problem under fuzzy environment. In This study the proposed algorithm is designed to treat opinions of experts, also can be used to solve a job shop environment under the existence of alternate operations. On the basis of the proposed method, an example is presented.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.319-322
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• 2004

물류/택배업계의 공급사슬관리에서 차량에 의한 고객의 요구 서비스 시간대 만족은 고객의 재고수준을 낮추고 또한 서비스 수준의 향상에 매우 중요한 제약조건이다. 최근에 소개된 메타휴리스틱인 개미해법(Ant Colony Optimization: ACO)은 NP-hard 문제의 해공간 탐색에 있어서 상당한 장점을 가지고 있으나, 시간대 제약이 있는 차량경로문제(Vehicle Routing Problems with Time Windows: VRPTW)에 대한 적용은 아주 미비한 실정이다. 따라서, 본 연구에서는 ACO 를 VRPTW에 적용하여 최선의 차량경로 해를 구하기 위한 여러 변형을 제시하고, 이들의 영향을 다양한 실험문제를 이용하여 분석하고자 한다. 계산실험 결과, 기본 ACO 에 여러 설계 요소들을 추가함에 따라 계산시간이 다소 증가하지만 보다 우수한 차량경로 해를 구할 수 있었다.

• 한국경영과학회지
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• 제26권2호
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• pp.13-46
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• 2001

SDP (Semidefinite Programming), as a sort of “cone-LP”, optimizes a linear function over the intersection of an affine space and a cone that has the origin as its apex. SDP, however, has been developed in the process of searching for better solution methods for NP-hard combinatorial optimization problems. We surveyed the basic theories necessary to understand SDP researches. First, We examined SDP duality, comparing it to LP duality, which is essential for the interior point method, Second, we showed that SDP can be optimized from an interior solution in polynomial time with a desired error limit. finally, we summarized several research papers that showed SDP can improve solution methods for some combinatorial optimization problems, and explained why SDP has become one of the most important research topics in optimization. We tried to integrate SDP theories. relatively diverse and complicated. to survey research papers with our own perspective, and thus to help researcher to pursue their SDP researches in depth.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.609-612
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• 2000

Job-shop scheduling problem(JSSP) is one of the best-known machine scheduling problems and essentially an ordering problem. A new encoding scheme which always give a feasible schedule is presented, by which a schedule directly corresponds to an assigned-operation ordering string. It is initialized with G&T algorithm and improved using the developed genetic operator; APMX or BPMX crossover operator and mutation operator. and the problem of infeasibility in genetic generation is naturally overcome. Within the framework of the newly designed genetic algorithm, the NP-hard classical job-shop scheduling problem can be efficiently solved with high quality. Moreover the optimal solutions of the famous benchmarks, the Fisher and Thompson's 10${\times}$10 and 20${\times}$5 problems, are found.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1065-1070
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• 2003

Facility Layout Planning is concerned with how to arrange facilities necessary for production in a given space. Its objective is often to minimize the total sum of all material flows multiplied by the distance among facilities. FLP belongs to NP complete problem; i.e., the number of possible layout solutions increases with the increase of the number of facilities. Thus, meta heuristics such as Genetic Algorithm (GA) and Simulated Annealing have been investigated to solve the FLP problems. However, one of the biggest problems which lie in the existing meta heuristics including GA is hard to find an appropriate combinations of parameters which result in optimal solutions for the specific problem. The Ant System algorithm with elitist and ranking strategies is used to solve the FLP problem as an another good alternative. Experimental results show that the AS algorithm is able to produce the same level of solution quality with less sensitive parameters selection comparing to the ones obtained by applying other existing meta heuristic algorithms.

• 대한산업공학회지
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• 제40권3호
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• pp.305-312
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• 2014

This research deals with a problem that minimizes makespan in a non-identical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is large, we propose four heuristic algorithms including genetic algorithm based heuristics to solve the practical big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.

• 한국경영과학회지
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• 제17권3호
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• pp.137-158
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• 1992

We study the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are pnelized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. We develop Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP. In addition, several heuristic algorithms are presented and performances are tested using computational experiments. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We also present a method to phase into a target cyclic schedule for infinite horizon problems. These can be used as a practical scheduling tool for temporarily overloaded facilities or to reschedule production after a disruption.

• 한국산업정보학회논문지
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• 제13권5호
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• pp.142-148
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• 2008

Facility Layout Planning is concerned with how to arrange facilities necessary for production in a given space. Its objective is often to minimize the total sum of all material flows multiplied by the distance among facilities. FLP belongs to NP complete problem; i.e., the number of possible layout solutions increases with the increase of the number of facilities. Thus, meta heuristics such as Genetic Algorithm (GA) and Simulated Annealing have been investigated to solve the FLP problems. However, one of the biggest problems which lie in the existing meta heuristics including GA is hard to find an appropriate combinations of parameters which result in optimal solutions for the specific problem. The Ant System algorithm with elitist and ranking strategies is used to solve the FLP problem as an another good alternative. Experimental results show that the AS algorithm is able to produce the same level of solution quality with less sensitive parameters selection comparing to the ones obtained by applying other existing meta heuristic algorithms.