• 산업공학
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• 제17권spc호
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• pp.20-27
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• 2004

A flexible assembly system (FAS) is a production system that assembles various parts with many constraints and manufacturing flexibilities. This paper presents a new method for efficiently solving the integrated process planning and scheduling in FAS. The two problems of FAS process planning and scheduling are tightly related with each other. However, in almost all the existing researches on FAS, the two problems have been considered separately. In this research, an endosymbiotic evolutionary algorithm is adopted as methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary algorithm to solving the integrated problem. Some evolutionary schemes are used in the algorithm to promote population diversity and search efficiency. The experimental results are reported.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.239-242
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• 2000

Symbiotic evolutionary algorithms are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual requires first selecting symbiotic partners of the individual. The symbiotic partner effects the change of individual's fitness and search direction. In this study we are to analyze how much partnering strategies can influence the performance of the algorithms. For this goal extensive experiments are carried out to compare the performance of partnering strategies. The NKC model and the binary string covering problem are used as the test-bed problems. The experimental results indicate that there does not exist statistically significant difference in their performance.

• 대한산업공학회지
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• 제30권2호
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• pp.130-145
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• 2004

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

• 한국경영과학회지
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• 제26권4호
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• pp.109-124
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• 2001

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed model assembly lines (MMALs). Line balancing and model sequencing are important for an efficient use of MMALs. The two problems of balancing and sequencing MMALs are tightly related with each other. However, In almost all the existing researches on mixed-model production lines, the two problems have been considered separately. In this research, an endosymbiotic evolutionary a1gorithm, which is a kind of coevolutionary a1gorithm, is adopted as a methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary a1gorithm to solving the integrated problem. Some evolutionary schemes are used In the a1gorithm to promote population diversity and search efficiency. The proposed a1gorithm is compared with the existing evolutionary algorithms in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

• 한국경영과학회지
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• 제26권2호
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• pp.47-58
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• 2001

The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in shortest path problem (SPP) using evolutionary algorithms. The problem of finding the k-MVAs in SPP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the shortest distance between two specified nodes. Generally, the problem of determining the k-MVAs in SPP has been known as NP-hard. Therefore, to deal with problems of the real world, heuristic algorithms are needed. In this study we present three kinds of evolutionary algorithms for finding the k-MVAs in SPP, and then to evaluate the performance of proposed algorithms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.573-576
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• 2006

This paper deals with multi-objective optimization problem of finding a set of well-distributed solutions close to the true Pareto optimal solutions. In this paper, we present a two-leveled symbiotic evolutionary algorithm to efficiently solve the problem. Most of the existing multi-objective evolutionary algorithms (MOEAs) operate one population that consists of individuals representing the complete solution to the problem. The proposed algorithm maintains several populations, each of which represents a partial solution to the entire problem, and has a structure with two levels. The parallel search and the structure are intended to improve the capability of searching diverse and good solutions. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The experimental results confirm the effectiveness of the proposed algorithm.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.930-935
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• 2002

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problem are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed­model production lines, the two problems have been considered separately. In 1his research, an endosymbiotic evolutionary algorithm, which is a kind of evolutionary algorithm, is adopted as a methodology in order to solve the two problems simultaneously. Some evolutionary search capability, rapidity of convergence and population diversity. The proposed algorithm is compared with the existing evolutionary algorithm in terms of solution quality. The experimental results confirm the effectiveness of our approach.

• 한국경영과학회지
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• 제28권2호
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• pp.1-15
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• 2003

This paper presents a new evolutionary algorithm to solve complex multi-level integration problems, which is called multi-level symbiotic evolutionary algorithm (MEA). The MEA uses an efficient feedback mechanism to flow evolution information between and within levels, to enhance parallel search capability, and to improve convergence speed and population diversity. To show the MEA's applicability, It is applied to the integrated planning of production and distribution in supply chain management. The encoding and decoding methods are devised for the integrated problem. A set of experiments has been carried out, and the results are reported. The superiority of the algorithm's performance is demonstrated through experiments.

• 대한산업공학회지
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• 제29권1호
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• pp.65-77
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• 2003

This paper addresses FMS(Flexible Manufacturing System) loading problems with machine, tool and process flexibilities. When designing FMS planning, it is important to take account of these flexibilities for an efficient utilization of the resources. However, almost all the existing researches do not appropriately consider various flexibilities due to the problem complexity. This paper presents a new evolutionary algorithm to solve the FMS loading problems with machine, tool and process flexibilities. The algorithm is named a multi-level symbiotic evolutionary algorithm. The proposed algorithm is compared with the existing ones in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

• Composites Research
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• 제12권4호
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• pp.42-54
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• 1999

섬유-금속 적층 복합재료(FMLC)는 섬유와 금속 박판으로 구성된 새로운 형태의 구조재로 가볍고 우수한 피로 특성을 가지며 금속과 같이 가소성과 충격저항성이 우수하고, 가공성이 뛰어나다. 본 연구에서는 여러 하중 조건하에 있는 섬유-금속 적층 복합재료를 유전자 알고리듬을 이용하여 최적 설계하였다. 전단변형이론에 근거한 유한요소법을 사용하여 적층판을 해석하였으며, 설계변수로 금속판의 강도와 섬유 층의 수에 따른 적층각도를 두었다. 섬유층과 금속판의 적합도 함수로는 각각 Tasi-Hill failure criterion과 Miser yield criterion을 사용하였다. 유전자 알고리듬의 연산자로는 토너먼트 선택과 균일 교배를 사용하였다. 효율적인 진화를 위해 엘리티스트 모델을 사용하며, 높은 정확도를 가진 해를 얻기 위해 크리프 무작위 탐색(creeping random search) 방법을 통해 더 우수한 자손을 얻었다. 여러 가지 하중 조건에 대하여 최적설계 결과를 나타내었으며, 파괴 지수 측면에서 탄소섬유강화복합재료(CFRP)와 비교하였다. 해석 결과 섬유-금속 적층 복합재료는 탄소섬유강화복합재료에 비하여 집중하중이나 분포하중 형태에 대하여 우수한 특성을 보였으며, 파괴 지수의 편차가 적어 예기치 않은 하중에 잘 견딜 것으로 사료된다.