• 산업경영시스템학회지
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• 제20권41호
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• pp.1-14
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• 1997

This study proposes a genetic algorithm using Pr(equation omitted)fer number for the traveling salesman problem(PNGATSP). Nearest neighbor nodes are mixed with randomly selected nodes at the stage of generating initial solutions. Proposed PNGATSP adopts a few ideas which are different from traditional genetic algorithms. For instance, an exponential fitness function and elitism are used and Pr(equation omitted)fer number is used for encoding TSP. Genetic operators are selected by experiments, which make a good solution among four combinations of conventional genetic operators and new genetic operators. For respective combinations, robust set of parameters is determined by the experimental designing approach. The feature of Pr(equation omitted)fer number code for TSP and the search power of GA using Pr(equation omitted)fer number is analysed. The best is a combination of OX(order crossover) and swap, which is superior to the other experimented combinations of genetic operators by 1.0%∼12.8% deviation.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2009년도 추계학술발표논문집
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• pp.574-577
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• 2009

본 논문은 외판원 문제(TSP: Traveling Salesman Problem)를 이용하여 로봇중심의 FMC(Flexible Manufacturing Cell)에서 반송 로봇의 작업순서를 설계하는 방법을 제시하였다. 이를 위해, 먼저 다수의 설비와 반송 로봇으로 구성된 대표적인 로봇 중심의 FMC를 가상으로 설계한 후, 실험계획법을 이용하여 다양한 조건에서의 주요 반응변수들의 인과관계를 규명하였다. 실험결과, 처리량, 반송로봇의가동률, 그리고 Buffer의 평균 대기 작업물의 수가 주요 반응변수들로 선정되었으며, 이를 기반으로 순서기반 조합최적화 문제인 TSP로 로봇 작업순서를 설계하였다. 제안한 방법과 기존의 방법을 비교하기 위해서 시뮬레이션을 수행 한 결과 제안된 TSP 방법이 기존의 방법 보다 반송 로봇의 교착 (Deadlock) 상태를 방지하여 처리량 등 주요 반응변수들 모두를 향상 시키는 결과를 가져왔다. 더불어,이 방법은 본 연구에서 제시한 FMC 뿐 아니라 반도체나 LCD(Liquid Crystal Display) 생산 공정과 같이 반송 로봇에 의해 구성되어 있는 장치 산업분야에 적용가능하다는 측면에서 큰 효과가 기대된다.

• 대한산업공학회지
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• 제27권1호
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• pp.18-24
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• 2001

This paper presents a model and a heuristic algorithm for the Traveling Salesman Problem with Time Windows(TSPTW). The main difference of our model compared with the previous ones lies in that the time windows we are concerned are more flexible and realistic than the previous ones. In the typical TSPTW, the service at a node must begin within the time grid called the time window that is defined by the earliest and the latest time to start the service at each node. But, in real business practice, a lateness cost is usually penalized rather than the service is prohibited at all when a vehicle arrives after the latest time. Considering this situation, we develop a model with a new time window that allows an arrival after the latest time and penalizes the late arrival by charging a lateness cost. A two-phased heuristic algorithm is proposed for the model and is extensively tested to verify the accuracy and efficiency of the algorithm.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2000년도 추계학술발표논문집 (하)
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• pp.1373-1376
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• 2000

외판원 문제(Traveling Salesman Problem)는 주어진 n개의 도시들과 그 도시들간의 거리 비용이 주어졌을 매, 처음 출발도시에서부터 정확히 한 도시는 한 번씩만 방문하여 다시 출발도시로 돌아오면서 방문한 도시들을 연결하는 최소의 비용이 드는 경로를 찾는 문제로 최적해(optimal value)를 구하는 것은 전형적인 NP-완전 문제중의 하나이다[2,4,5, 8]. 따라서 이들의 수행시간을 줄이고자 하는 연구가 많이 진행된다. 본 논문에서는 외판원 문제의 최적의 해를 구하는데. 휴리스틱 알고리즘인 최근접 휴리스틱을 이용한다. 물론 수행 시간을 줄이고자 최적화 문제에서 좋은 성능을 보이는 유전 알고리즘 (Genetic Algorithm)으로 얻은 근사해(near optimal)를 초기 분기 함수로 사용하고, 근거리 통신망(Local Area Network)에 기반한 분산 처리 환경에서 여러 프로세서에 분산시켜 병렬성을 살린다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.61-67
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• 2008

This paper introduces the multi-vehicle routing problem(MRP) which is different from the traveling sales problem(TSP), and presents the ant system(AS) applied to the MRP. The proposed MRP is a distributive model of TSP since many vehicles are used, not just one salesman in TSP and even some constraints exist. In the AS, a set of cooperating agents called vehicles cooperate to find good solutions to the MRP. To make the proposed MRP extended more, Tokyo city model(TCM) is proposed. The goal in TCM is to find a set of routes that minimizes the total traveling time such that each vehicle can reach its destination as soon as possible. The results show that the AS can effectively find a set of routes minimizing the total traveling time even though the TCM has some constraints.

• Industrial Engineering and Management Systems
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• 제9권2호
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• pp.80-87
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• 2010

As express courier market expands rapidly, companies are exposed to fierce competition. To cope with struggle for their survival, they are continuously making efforts to improve their service system. Even if most of service centers are directly linked to a consolidation terminal in courier service network, some of them with regional disadvantages are operated in milk run type from/to the consolidation terminal, which is a traditional PDP (Pick-up and Delivery Problem). This study suggests an approach to solve the PDP with the objective of maximizing the incremental profit, which belongs to PTP (Profitable Tour Problem) class. After the PTP is converted to TSP (Traveling Salesman Problem) with the same objective, a heuristic algorithm based on GA (Genetic Algorithm) is developed and examined through an example problem in practice of a courier service company in Korea.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.518-518
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• 1996

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.385-386
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• 2009

• 산업경영시스템학회지
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• 제39권4호
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• pp.81-89
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• 2016

Distributed genetic algorithm (DGA), also known as island model or coarse-grained model, is a kind of parallel genetic algorithm, in which a population is partitioned into several sub-populations and each of them evolves with its own genetic operators to maintain diversity of individuals. It is known that DGA is superior to conventional genetic algorithm with a single population in terms of solution quality and computation time. Several researches have been conducted to evaluate effects of parameters on GAs, but there is no research work yet that deals with structure of DGA. In this study, we tried to evaluate performance of various genetic algorithms (GAs) for the famous symmetric traveling salesman problems. The considered GAs include a conventional serial GA (SGA) with IGX (Improved Greedy Crossover) and several DGAs with various combinations of crossover operators such as OX (Order Crossover), DPX (Distance Preserving Crossover), GX (Greedy Crossover), and IGX. Two distinct immigration policies, conventional noncompetitive policy and newly proposed competitive policy are also considered. To compare performance of GAs clearly, a series of analysis of variance (ANOVA) is conducted for several scenarios. The experimental results and ANOVAs show that DGAs outperform SGA in terms of computation time, while the solution quality is statistically the same. The most effective crossover operators are revealed as IGX and DPX, especially IGX is outstanding to improve solution quality regardless of type of GAs. In the perspective of immigration policy, the proposed competitive policy is slightly superior to the conventional policy when the problem size is large.

• 한국정보과학회논문지:시스템및이론
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• 제29권7호
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• pp.377-383
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• 2002

외판원 문제는 잘 알려진 NP-완전 문제로, 최적해(optimal value)를 구하는 다양한 알고리즘들이 개발되었다. 그러나 최악의 경우 지수 시간이 걸리므로 수행시간을 줄이는 다양한 방법들이 제안되고 있다. 최근접 휴리스틱 알고리즘은 최적해를 구하는 다른 알고리즘들에 비해 구조가 비교적 간단하다. 따라서 본 논문에서는 외판원 문제(Traveling Salesman Problem, TSP)의 최적해를 구할 수 있는 분기 함수(bounding function)를 적용한 분산 최근접 휴리스틱(nearest neighbor heuristic) 알고리즘을 PVM(Parallel Virtual Machine)에서 제공하는 마스터/슬래이브(master/slave) 모델을 사용하여 설계하고 구현하였다. 먼저 최적해를 찾는 수행 시간을 줄이기 위해 최적화 문제에서 좋은 성능을 보이는 분산 유전 알고리즘(distributed genetic algorithm)을 수행해 얻은 근사해(near optimal)를 초기 분기 함수로 사용한다. 특히 더욱 좋은 근사해를 구하고자 유전 연산자인 돌연변이를 새롭게 변형하여 적용하였다.