• International Journal of Quality Innovation
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• 제2권2호
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• pp.101-120
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• 2001

In this paper jobshop scheduling problem was considered on automated manufacturing systems with the closed loop and unidirectional material handling system. The objective of this research is to develop and evaluate heuristic scheduling procedures to improve productivity by minimizing makespan. Especially travel time of material handling system as well as processing time was considered in the proposed algorithms, A new heuristic algorithms are proposed and illustrates the proposed algorithm. The heuristic algorithms are implemented for various cases. The results show that the proposed algorithms provide better solutions in productivity, frequency, job waiting time and the number of waiting jobs than the random scheduling algorithm.

• Structural Engineering and Mechanics
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• 제52권2호
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• pp.405-426
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• 2014

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

• 한국컴퓨터정보학회논문지
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• 제22권9호
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• pp.81-89
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• 2017

The CRP(Container Relocation Problem) algorithms pursuing efficient container relocation of wharf container terminal can not be deterministic because of the large number of layout cases. Therefore, the CRP algorithms should adopt trial and error intuition and experimental heuristic techniques. And because the heuristic can not be best for all individual cases, it is necessary to find metrics which show excellent on average. In this study, we analyze GLAH(Greedy Look-ahead Heuristic) algorithm which is one of the recent researches in detail, and propose a heuristic metrics HOB(sum of the height differences between a badly placed container and the containers prohibited by the badly placed container) to improve the algorithm. The experimental results show that the improved algorithm, GLAH', exerts a stable performance increment of up to 3.8% in our test data, and as the layout size grows, the performance increment gap increases.

• 한국정보처리학회논문지
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• 제6권9호
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• pp.2311-2319
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• 1999

병렬 컴퓨팅에 있어 NP-complete 문제인 태스크 할당문제에 대한 두 가지 휴리스틱 알고리즘을 제시한다. 할당문제는 분산 메모리 멀티컴퓨터의 멀티 프로세싱 노드에 다중통신 태스크들을 최적의 매핑을 찾는 것이다. 태스크들을 목표 시스템 구조의 노드들에 매핑시키는 목적은 해법 품질에 손상 없이 병렬 실행시간을 최소화하기 위함이다. 많은 휴리스틱 기법들이 만족한 매핑을 얻기 위해 채택되어 왔다. 본 논문에서 제시되는 휴리스틱 기법은 유전자 알고리즘(GA)과 시뮬레이티드 어닐링(SA) 기법에 기반을 둔다. 매핑 설정을 위한 총 계산 비용으로 목적함수를 수식화하고 휴리스틱 알고리즘들의 성능을 평가한다. 랜덤, 그리디, 유전자, 어닐링 알고리즘들을 사용하여 얻은 해법의 품질과 시간을 비교한다. 할당 알고리즘 시뮬레이션 연구를 통한 실험적 결과를 보여준다.

• 한국정밀공학회지
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• 제12권6호
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• pp.27-36
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• 1995

This paper covers algorithms to determine a machine assignment strategy to locations on a single straight track by minimizing the total backtrack distance. Three different algorithms ar presented: an efficient heuristic procedure, the branch-and-bound algorithm, and the nerual network approach. Simulation results show that the proposed algorithms have potential power to design an on-line optimizer.

• 한국정보처리학회논문지
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• 제4권10호
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• pp.2477-2484
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• 1997

$A^{\ast}$와 같은 Best-first 휴리스틱 탐색 알고리즘들은 인공지능 분야에서 많은 문제를 해결하는데 가장 중요한 기법들 중의 하나이다. 휴리스틱 탐색의 공통적 특성은 계산의 복잡도가 매우 높다는 것이며, 이는 수많은 노드를 가진 지도에서 경로를 찾는 것과 같은 실질적인 문제 영역에 적용되기 어렵다는 것을 나타낸다. 본 논문에서는, 몇몇 휴리스틱 탐색 알고리즘이 언급되고, path-sensitive heuristic이라 불리는 새로운 동적 가중치 휴리스틱 방법이 제안되었다. 이 방법은 동적 가중치 휴리스틱에 기초하였고, 동적 휴리스틱은 admissible heuristic을 허용하지 않거나 휴리스틱의 정확도가 떨어지는 실제 문제 영역에서 탐색 노력을 줄이는데 사용될 수 있다. 탐색 과정 동안 ${\omega}$(가중치)가 동적으로 조정된다는 점에서, 다른 동적 가중치 휴리스틱 알고리즘과 구분된다.

• 정보처리학회논문지B
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• 제18B권2호
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• pp.73-82
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• 2011

메타 휴리스틱 알고리즘을 이용해 TSP (Traveling Salesman Problem) 문제를 풀고자 하는 많은 시도가 이루어지고 있다. TSP 문제는 대표적인 NP_Hard 문제로 탐색 알고리즘이나 최적화 알고리즘을 실험하는데 많이 사용되고 있으며, 복잡한 사회의 많은 문제들의 표준 모델로 제시되고 있다. 본 논문에서는 2009년 제안된 MINE 알고리즘을 TSP 에 적용시켜 메타 휴리스틱 알고리즘으로서의 탐색성능을 알아보고자 하였다. 이에 S-MINE (Search - MINE) 알고리즘을 제안하였으며, TSP 에 적용하여 그 결과를 고찰하였다.

• 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.

• 한국국방경영분석학회지
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• 제27권2호
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• pp.25-36
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• 2001

In this paper a new heuristic algorithm has been developed and presented for logistics for multiple objectives in an automated manufacturing systems. We proposed Simallest Processing and Average setup time Ratio First(SPARF) algorithm for multiple criteria under sequence setup time. The heuristic algorithm is implemented on the various problem cases by number of jobs and machines. The proposed algorithm provided smaller than the previously documented heuristics. The results obtained show a superior solution by the new heuristic over previous heuristics on all problem sizes. we perform analyses of variance to fortify the above results of comparison with the previous algorithms to the four cases using Statistical Analysis System(SAS) package. The results show that the larger is the number of groups or cells, the bigger is the amount of improvement by the proposed algorithms. It suggests that the algorithms proposed is strongly influenced by the number of cells, groups and interaction of these factors.

• 산업경영시스템학회지
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• 제24권68호
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• pp.21-30
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• 2001

The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in the minimum spanning tree problem(MSTP) using evolutionary algorithms. The problem of finding the k-MVAs in MSTP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the total length of minimum spanning tree. Generally, the problem which determine the k-MVAs in MSTP has known as NP-hard. Therefore, in order to deal with the problem of real world the heuristic algorithms are needed. In this study we propose to three genetic algorithms as the heuristic methods for finding the k-MVAs in MSTP. The algorithms to be presented in this study are developed using the library of the evolutionary algorithm framework(EAF) and the performance of the algorithms are analyzed through the computer experiment.