• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.304-315
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• 2018

Harmony Search (HS) is a recently developed metaheuristic algorithm that is widely known to many researchers. However, due to the increasing complexity of optimization problems, the optimal solution cannot be efficiently found by HS. To overcome this problem, there have been many studies that have improved the performance of HS by modifying the parameter settings and incorporating other metaheuristic algorithms. In this study, Copycat HS (CcHS) is suggested, which improves the parameter setting method and the performance of searching for the optimal solution. To verify the performance of CcHS, the results were compared to those of HS variants with a set of well-known mathematical benchmark problems. The effectiveness of CcHS was proven by finding final solutions that are closer to the global optimum than other algorithms in all problems. To analyze the applicability of CcHS to engineering optimization problems, it was applied to a design problem for Water Distribution Systems (WDS), which is widely applied in previous research. As a result, CcHS proposed the minimum design cost, which was 21.91% cheaper than the cost suggested by simple HS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.1-12
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• 2016

The Harmony Search Algorithm (HSA) is one of the recently developed metaheuristic optimization algorithms. Since the development of HSA, it has been applied by many researchers from various fields. The increasing complexity of problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms are required. In this study, to improve the HSA in terms of a structural setting, a new HSA that has structural characteristics, called the Multi-layered Harmony Search Algorithm (MLHSA) was proposed. In this new method, the structural characteristics were added to HSA to improve the exploration and exploitation capability. In addition, the MLHSA was applied to optimization problems, including unconstrained benchmark functions and water distribution system pipe diameter design problems to verify the efficiency and applicability of the proposed algorithm. The results revealed the strength of MLHSA and its competitiveness.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.183-192
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• 2022

With the growth of the packaging industry, demand on the packaging printing comes in various forms. Customers' orders are diversifying and the standards for quality are increasing. Offset printing is mainly used in the packaging printing since it is easy to print in large quantities. However, productivity of the offset printing decreases when printing various order. This is because it takes time to change colors for each printing unit. Therefore, scheduling that minimizes the color replacement time and shortens the overall makespan is required. By the existing manual method based on workers' experience or intuition, scheduling results may vary for workers and this uncertainty increase the production cost. In this study, we propose an automated scheduling method of parallel offset printing process for packaging printing. We decompose the original problem into assigning and sequencing orders, and ink arrangement for printing problems. Vehicle routing problem and assignment problem are applied to each part. Mixed integer programming is used to model the problem mathematically. But it needs a lot of computational time to solve as the size of the problem grows. So guided local search algorithm is used to solve the problem. Through actual data experiments, we reviewed our method's applicability and role in the field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.157-164
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• 2023

This paper suggests O(n²) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(T_e) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate _minr_w(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate _minr_fi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.793-796
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• 2008

본 논문은 생산 물류 시스템최적화의 실현에 가장 대표적인 생산수송계획문제인 수송문제(TP: Transportation Problem)에 고정비용을 고려한 고정비용 수송문제(fcTP: Fixed charge Transportation Problem)를 다룬다. 특히 NP-hard문제로 널리 알려진 TP에서 수송량에 비례하는 가변비용과 함께 추가적으로 모든 경로에서 발생하는 고정비용을 함께 고려한 fcTP를 다룬다. 따라서 이러한 fcTP를 해결하기 위해 메타 휴리스틱기법 중에 가장 널리 이용되고 있는 유전 알고리즘(CA: Genetic Algorithm)을 이용한 해법을 제시하고자 한다. 본 논문에서는 CA를 이용해 고정비용 수송문제의 해를 우선순위기반 유전자 표현법을 이용해 fcTP에 적용해 보고 수치 실험을 통해 그 성능에 대한 연구를 한다.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.636-643
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• 2020

The differential evolution algorithm is one of the meta-heuristic techniques developed to solve the real optimization problem, which is a continuous problem space. In this study, in order to use the differential evolution algorithm to solve the traveling salesman problem, which is a discontinuous problem space, a random key representation method is applied to the differential evolution algorithm. The differential evolution algorithm searches for a real space and uses the order of the indexes of the solutions sorted in ascending order as the order of city visits to find the fitness. As a result of experimentation by applying it to the benchmark traveling salesman problems which are provided in TSPLIB, it was confirmed that the proposed differential evolution algorithm based on the random key representation method has the potential to solve the traveling salesman problems.

• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1416-1427
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• 2012

This paper proposes a design technique of a survivable ship backbone network, which describes a near optimal configuration scheme of physical and logical topologies of which the survivable ship backbone network consists. We first analyze and present an efficient architecture of a survivable ship backbone network consisting of redundant links and ship devices with dual communication interfaces. Then, we present an integer linear programming-based configuration scheme of a physical topology with regard to the proposed ship backbone network architecture. Finally, we present a metaheuristic-based configuration scheme of a logical topology, underlying the physical topology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.969-972
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• 2007

수송문제는 산업공학 및 전자계산학 분야에서 중요한 문제 중의 하나로 인식된다. 수송문제가 시설을 수립하거나 고객들의 요구를 이행하기 위한 추가적인 고정 비용과 연관될 때, 이를 고정비용을 고려한 비선형 수송문제(Fixed Charge Non-linear Transportation Problem)라 한다. 고정비용을 고려한 비선형 수송문제는 한 종류의 상품을 다수의 공급처에서 다수의 수급처로 수송할 때, 수송비용과 고정비용이 최소가 되도록 수송량을 결정하는 문제이다. 본 논문에서는 이 비선형 수송문제에 가장 많이 쓰이는 메타 휴리스틱 방법들 중 유전 알고리즘을 이용한 해법을 제시한다. 유전 알고리즘을 적용함에 있어서 가장 중요한 것 중에 하나는 해의 유전자표현을 어떻게 나타낼 것인가 인데, 본 논문에서는 수송문제의 해를 걸침나무로 표현할 수 있다는 점에 착안하여 유전자 표현법들을 수송문제에 적용해 보고 수치 실험을 통해 그 성능에 대한 비교를 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1715-1724
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• 2013

The maximum lifetime data aggregation problem is to maximize the network lifetime as minimizing the transmission energy of all deployed nodes in wireless sensor networks. In this paper, we propose a simulated annealing algorithm to solve efficiently the maximum lifetime data aggregation problem on the basis of meta-heuristic approach in wireless sensor networks. In order to make a search more efficient, we propose a novel neighborhood generating method and a repair function of the proposed algorithm. We compare the performance of the proposed algorithm with other existing algorithms through some experiments in terms of the network lifetime and algorithm computation time. Experimental results show that the proposed algorithm is efficient for the maximum lifetime data aggregation problem in wireless sensor networks.