• 경영과학
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• 제26권1호
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• pp.209-223
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• 2009

In this paper, an analysis problem of repair levels and spare part allocation for MIME(Multi indenture multi echelon) systems is studied using simulation and meta-heuristics. We suggest a method to determine simultaneously repair levels and spare parts allocation to minimize the life cycle cost of MIME system under availability constraint. A simulated annealing method is used to analyze the repair levels and genetic algorithm is used to obtain the optimal allocation of spare parts. We also develop a simulation system to calculate the life cycle cost and system availability. Some numerical examples are also studied.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3772-3783
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• 2021

This work proposes a new efficient meta-heuristic optimization algorithm called Gamma Ray Interactions Based Optimization (GRIBO). The algorithm mimics different energy loss processes of a gamma-ray photon during its passage through a matter. The proposed novel algorithm has been applied to search for the global minima of 30 standard benchmark functions. The paper also considers solving real optimization problem in the field of nuclear engineering, radioisotope identification. The results are compared with those obtained by the Particle Swarm Optimization, Genetic Algorithm, Gravitational Search Algorithm and Grey Wolf Optimizer algorithms. The comparisons indicate that the GRIBO algorithm is able to provide very competitive results compared to other well-known meta-heuristics.

• 산업경영시스템학회지
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• 제30권3호
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• pp.94-102
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• 2007

In this paper, we consider a line balancing problem in hybrid flowshops where each workstation has identical parallel machines. The number of machines in each workstation is determined in ways of satisfying pre-specified throughput rate of the system. To minimize the total number of machines in the systems, we propose five heuristic methods and one simulated annealing method. Extensive computational experiments found the superiorities of two heuristic methods and the meta-heuristic.

• 한국산업정보학회논문지
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• 제27권1호
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• pp.37-48
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• 2022

본 연구에서는 공학설계 최적화 문제 해결을 위한 혼합 메타휴리스틱(Hybrid Meta-heuristic) 접근법을 제안된다. 공학 설계 최적화 문제는 다양한 형태의 변수를 가지며, 복잡한 제약조건들하에서 그 최적해를 구하는 문제로 이미 많은 기존 연구들을 통해 다양한 접근법들이 개발되어져 왔다. 하지만 그 효율성은 아직까지 크게 개선되지 못하고 있는 실정이다. 따라서 본 연구에서는 이러한 효율성을 개선하기 위한 새로운 접근법을 제안한다. 제안된 혼합 메타휴리스틱 접근법은 탐색 공간에 대한 전역적 탐색을 위해 유전알고리즘(Genetic Algorithm: GA) 접근법, 지역적 탐색을 위해 변동이웃탐색(Variable Neighborhood Search: VNS) 접근법과 언덕오르기(Hill Climbing: HC) 접근법을 혼합(GA-VNS-HC)하였다. 사례 연구에서는 다양한 형태의 공학설계 최적화 문제를 이용하여 본 연구에서 제안한 GA-VNS-HC 접근법의 우수성을 입증하였다.

• Structural Engineering and Mechanics
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• 제58권3호
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• pp.533-553
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• 2016

In this paper, the recently developed meta-heuristic algorithm called tug of war optimization is applied to optimal design of castellated beams. Two common types of laterally supported castellated beams are considered as design problems: beams with hexagonal openings and beams with circular openings. Here, castellated beams have been studied for two cases: beams without filled holes and beams with end-filled holes. Also, tug of war optimization algorithm is utilized for obtaining the solution of these design problems. For this purpose, the minimum cost is taken as the objective function, and some benchmark problems are solved from literature.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.409-412
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• 2004

Today, meta-heuristic algorithms have been much attention by researcher because they have the power of solving combinational optimization problems efficiently. As the result, many variants of a meta-heuristic algorithm (e.g., simulated annealing) have been proposed for specific application domains. However, there are few efforts to classify them into a unified software framework, which is believed to provide the users with the reusability of the software, thereby significantly reducing the development time of algorithms. In this paper, we present an object-oriented framework to be used as a general tool for efficiently developing variants of simulated annealing algorithm. The interface classes in the framework achieve the modulization of the algorithm, and the users are allowed to specialize some of the classes appropriate for solving their problems. The core of the framework is Algorithm Configuration Pattern (ACP) which facilitates creating user-specific variants flexibly. Finally, we summarize our experiences and discuss future research topics.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.370-384
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• 2017

The image segmentation is the most important operation in an image processing system. It is located at the joint between the processing and analysis of the images. Unsupervised segmentation aims to automatically separate the image into natural clusters. However, because of its complexity several methods have been proposed, specifically methods of optimization. In our work we are interested to the technique SFLA (Shuffled Frog-Leaping Algorithm). It's a memetic meta-heuristic algorithm that is based on frog populations in nature searching for food. This paper proposes a new approach of unsupervised image segmentation based on SFLA method. It is implemented and applied to different types of images. To validate the performances of our approach, we performed experiments which were compared to the method of K-means.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1417-1426
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• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• Structural Engineering and Mechanics
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• 제53권5호
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• pp.847-865
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• 2015

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.9-12
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• 2000

컨테이너 터미널에서 효율적인 적하작업 계획을 자동으로 생성하는 알고리즘을 연구하였다. 실제 터미널에서 계획자들이 적하작업 계획시에 고려하는 제약소건 및 효율적인 계획을 위한 고려사항을 조사하였다. 이를 바탕으로 1단계에서는 개미시스템(ant system)이라는 인공지능기법을 적용하여 제약조건을 만족시키면서 원활한 적하작업이 진행될 수 있도록 컨테이너 크레인과 트랜스퍼 크레인의 이동순서와 위치를 결정하고, 2단계에서는 1단계에서의 결과를 바탕으로 빔탐색법(beam search)을 사용하여 컨테이너 개개의 작업순서를 결정하는 알고리즘을 개발하였다. 또한 개발된 시스템의 성능을 검증하기 위하여 최근의 대형선반에 대한 실제 현장자료를 바탕으로 실험을 수행하였다.