• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1699-1708
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• 2007

The optimal power flow(OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, the OPF problem has been intensively studied and widely used in power system operation and planning. In these days, OPF is becoming more and more important in the deregulation environment of power pool and there is an urgent need of faster solution technique for on-line application. To solve OPF problem, many heuristic optimization methods have been developed, such as Genetic Algorithm(GA), Evolutionary Programming(EP), Evolution Strategies(ES), and Particle Swarm Optimization(PSO). Especially, PSO algorithm is a newly proposed population based heuristic optimization algorithm which was inspired by the social behaviors of animals. However, population based heuristic optimization methods require higher computing time to find optimal point. This shortcoming is overcome by a straightforward parallel processing of PSO algorithm. The developed parallel PSO algorithm is implemented on a PC cluster system with 6 Intel Pentium IV 2GHz processors. The proposed approach has been tested on the IEEE 30-bus system. The results showed that computing time of parallelized PSO algorithm can be reduced by parallel processing without losing the quality of solution.

• Journal of Nutrition and Health
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• v.34 no.6
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• pp.701-714
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• 2001

The purpose of this study was to apply a PERT-type system, a combination of the project evaluation and review technique(PERT) and critical path method(CPM) on the employees' work time management of flood preparation, assembly, transportation and cleaning in home-delivered meals program for elderly The resources allotment heuristic program was developed by considering the number of employees and cooking utilities, being limited resources of home- delivered meals program. This program could assign the employees to perform the works included in flood preparation, assembly, transportation ind cleaning. Critical path and activities ware identified by PERT-type system on the basic of work time investigation in five senior centers. Work sheets were invented to perform the work by the shortest path with flexible employees'maximum flow As a result of the work time investigation, the most prevalent activities were ones of preparation in center C and E. Besides, the preparation(over fifty percent) was the most proportion among flood preparation, assembly, transportation and cleaning in center C and E. Critical path and activities of 'C'center were cucumber in sauce preparation path and assembly, wrapping in assembly path and case delivery in transportation path. Critical path and activities of 'E'center were Pan-fried Potato Preparation Path and assembly, case covering, wrapping in assembly Path. The work sheet invented by the heuristic program and PERT-type system reduced the work completion time and man hours in both centers.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.33 no.12
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• Advances in Computational Design
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• v.7 no.4
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• pp.297-319
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• 2022

Due to their natural and social revelation, also their ease and flexibility, human collective behavior and teamwork sports are inspired to introduce optimization algorithms to solve various engineering and scientific problems. Nowadays, meta-heuristic algorithms are becoming some striking methods for solving complex real-world problems. In that respect in the present study, the authors propose a novel meta-innovative algorithm based on soccer teamwork sport, suitable for optimization problems. The method may be referred to as the Soccer League Optimization-based Championship Algorithm, inspired by the Soccer league. This method consists of two main steps, including: 1. Qualifying competitions and 2. Main competitions. To evaluate the robustness of the proposed method, six different benchmark mathematical functions, and two engineering design problem was performed for optimization to assess its efficiency in achieving optimal solutions to various problems. The results show that the proposed algorithm may well explore better performance than some well-known algorithms in various aspects such as consistency through runs and a fast and steep convergence in all problems towards the global optimal fitness value.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1564-1574
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• 1999

In order to improve the efficiency of optimizing compilers, integration of register allocation and instruction scheduling has been extensively studied. One of the promising integration techniques is register allocation based on register-reuse chains. However, the generation of register-reuse chains in the previous approach was not completely systematic and consequently it creates unnecessarily dependencies that restrict instruction scheduling. This paper proposes a new register allocation technique based on a systematic generation of register-reuse chains. The first phase of the proposed technique is to generate register-reuse chains that are optimal in the sense that no additional dependencies are created. Thus, register allocation can be done without restricting instruction scheduling. For the case when the optimal register-reuse chains require more than available registers, the second phase reduces the number of required registers by merging the register-reuse chains. Chain merging always generates additional dependencies and consequently enforces the execution order of instructions. A heuristic is developed for the second phase in order to reduce additional dependencies created by merging chains. For matrix multiplication program, the number of registers resulting from the first phase is small enough to fit into available registers for most basic blocks. In addition, it is shown that the restriction to instruction scheduling is reduced by the proposed merging heuristic of the second phase.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.2
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• pp.124-131
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• 2011

In this research report, we propose a heuristic algorithm with some primal recovery strategies for capacitated facility location problems (CFLP), which is a well-known combinatorial optimization problem with applications in distribution, transportation and production planning. Many algorithms employ the branch-and-bound technique in order to solve the CFLP. There are also some different approaches which can recover primal solutions while exploiting the primal and dual structure simultaneously. One of them is a MVCD (Mean Value Cross Decomposition) ensuring convergence without solving a master problem. The MVCD was designed to handle LP-problems, but it was applied in mixed integer problems. However the MVCD has been applied to only uncapacitated facility location problems (UFLP), because it was very difficult to obtain "Integrality" property of Lagrangian dual subproblems sustaining the feasibility to primal problems. We present some heuristic strategies to recover primal feasible integer solutions, handling the accumulated primal solutions of the dual subproblem, which are used as input to the primal subproblem in the mean value cross decomposition technique, without requiring solutions to a master problem. Computational results for a set of various problem instances are reported.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.9-11
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• 1999

조합 최적화 문제인 Traveling Salesman problems(TSP)을 Genetic Algorithm(GA)과 Local Search Heuristic인 Lin-Kernighan(LK) Heuristic[2]을 이용하여 접근하는 것은 최적해를 구하기 위해 널리 알려진 방법이다. 이 논문에서는 LK를 이용하여 주어진 TSP 문제에서 Local Optima를 찾고, GA를 이용하여 Local Optimal를 바탕으로 Global Optima를 찾는데 이용하게 된다. 여기서 이런 GA와 LK를 이용하여 TSP 문제를 풀 경우 해가 점점 수렴해가면서 중복된 유전자가 많이 생성된다. 이런 중복된 유전자를 제거함으로써 탐색의 범위를 보다 넓고 다양하게 검색하고, 더욱 효율적으로 최적화를 찾아내는 방법에 대해서 논하겠다. 이런 방법을 이용하여 rat195, gil262, lin318의 TSP문제에서 효율적으로 수행된다.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.350-353
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• 1991

This study develops an expert system which solves the problems of the MTr/feeder overloads and the feeder constraints in automated radial distribution systems. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches which eliminates the system violation, while achieving the load balance of the MTrs/feeders. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in AI language Prolog. This system adopts the best-first tree search technique. The computational results are also prepared to show the performance of the heuristic algorithm developed.

• Journal of Information Processing Systems
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• v.13 no.2
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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.

• Structural Engineering and Mechanics
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• v.53 no.5
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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.