• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.89-97
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• 2016

This paper addresses the problem of the construction planning of artillery positions, for which we present an optimization model and propose a heuristic algorithm to solve problems of practical size. The artillery position construction plan includes the assignment of engineers to support the artillery and the schedule of the support team construction sequence. Currently, in the army, managers construct the plan based on their experience. We formulate the problem as a mixed integer program and present a heuristic that utilizes the decomposition of the mixed integer model. We tested the efficacy of the proposed algorithm by conducting computational experiments on both small-size test problems and large-size practical problems. The average optimality gap in the small-size test problem was 6.44% in our experiments. Also, the average computation time to solve the large-size practical problems consisting of more than 200 artillery positions was 79.8 seconds on a personal computer. The result of our computational experiments shows that the proposed approach is a viable option to consider for practical use.

• Journal of Navigation and Port Research
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• v.35 no.8
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• pp.657-665
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• 2011

This study deals with an integrated problem for deciding sequencing and storage location of export containers together at its receiving operation in the container terminal with a perpendicular layout. The preferred storage location of an export container varies with the priority of the corresponding loading operation and the waiting time of an external truck depends on its storage time. This paper proposes the mixed integer programming model considering the expected arrival time and expected finish time of an external truck and the preferred storage location for its loading operation. And we suggest the heuristic algorithm based on a simulated annealing algorithm for real world adaption. We compare the heuristic algorithm with the optimum model in terms of the computation times and total cost and the performance of the heuristic algorithm is analyzed through a numerical experiment.

• Tunnel and Underground Space
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• v.24 no.1
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• pp.11-20
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• 2014

This study analyzed the optimal routes of auxiliary vehicles in an open-pit mine that need to traverse the entire mine through many working points. Unlike previous studies which usually used the Dijkstra's algorithm, this study utilized a heuristic algorithm for the Traveling Salesman Problem(TSP). Thus, the optimal routes of auxiliary vehicles could be determined by considering the visiting order of multiple working points. A case study at the Pasir open-pit coal mine, Indonesia was conducted to analyze the travel route of an auxiliary vehicle that monitors the working condition by traversing the entire mine without stopping. As a result, we could know that the heuristic TSP algorithm is more efficient than intuitive judgment in determining the optimal travel route; 20 minutes can be shortened when the auxiliary vehicle traverses the entire mine through 25 working points according to the route determined by the heuristic TSP algorithm. It is expected that the results of this study can be utilized as a basis to set the direction of future research for the system optimization of auxiliary vehicles in open-pit mines.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.226-226
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• 2011

최적 저수지운영을 위한 운영률 도출이나 강우-유출 및 수질 모형의 매개변수 추정 문제처럼 비선형적이고 추정해야할 변수의 수가 많은 경우, 수학적으로 모형화하기에 너무 복잡해서 선형계획법, 비선형계획법, 동적계획법 등을 사용하여 최적해를 구할 수 없는 경우도 있다. 이러한 문제에 대해서는 구조적 진화를 통해 최적해를 구하는 방법들이 사용된다. 일반적으로 미지수의 개수가 많아지면 전역최적해를 찾기가 어려워진다. 전역최적해를 찾는 여러 가지 방법들이 수자원 분야에서는 강우-유출모형의 매개변수를 추정하는데 많이 사용되고 있으며, 특히 유전자 알고리즘, SCE-UA 알고리즘 등 전역최적해를 찾는 메타휴리스틱 방법이 많이 사용되고 있다. 전역최적화 방법을 개발하는 연구자들은 최적화방법의 성능을 평가하기 위해 다양한 검사함수(test function)를 만들어 성능을 평가하고 있다. 본 연구에 사용한 검사함수는 Mishra의 연구(2006a, 2006b)에서 사용한 중요하고 복잡한 검사함수이다. 유전자 알고리즘, SCE-UA 알고리즘, DDS 알고리즘을 검사함수 중 전역해를 찾기 어려운 2 차원 함수 2 가지, 다차원 함수 4 가지 함수에 적용하여 각각의 탐색 성능을 평가하였다. 2차원 함수인 Bukin 함수에 대해서는 모든 최적화 방법이 전역최적해를 찾을 수 없었지만, 유전자 알고리즘이 가장 전역최적해에 가까웠고 다음으로 DDS 알고리즘 순서였다. 지역수렴 영역이 많을 것으로 판단되는 10, 30, 50 차원 Michalewicz 함수에 대해서는 DDS 알고리즘으로 구한 최적해가 전역최적해와 매우 근접하였고 다음으로 SCE-UA 알고리즘, 유전자 알고리즘 순이었다. 지역수렴 영역이 상대적으로 다른 함수보다 넓은 10 차원 Schwefel 함수에 대해서는 DDS 알고리즘으로 구한 최적해가 전역최적해와 거의 근접하였고 유전자 알고리즘과 SCE-UA 알고리즘은 매우 큰 편차를 보였다. 40, 80 차원 Schwefel 함수에 대해서는 3 가지 알고리즘 모두 전역최적해와 편차를 보였지만 DDS 알고리즘에 의한 최적해와 다른 두 알고리즘에 의한 최적해는 1 오더(order) 정도의 차이가 났다. 지역수렴 영역이 큰 Michalewicz 함수와 Schwefel 함수에 대한 결과는 매우 흡사한 결과이다. 이상과 같은 결과로, 유전자 알고리즘은 매개변수의 수가 적을 경우 우수한 탐색성능을 가졌으며, SCE-UA 알고리즘은 Griewank, Rastrigin 함수와 같은 형태인 경우 우수한 성능을 보였다. DDS 알고리즘은 전체적으로 우수한 탐색 능력을 가진 것으로 판단된다. 그러므로 수위구간 영역별 저수지운영률 도출을 위한 적절한 최적화방법으로 DDS 알고리즘을 선정하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.137-141
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• 2005

Optimal path search algorithm should consider traffic flows of the roads as well as the distance between a departure and destination, The existing path search algorithms, however, usually don't apply the continuously changed traffic flows. In this paper, we propose a new optimal path search algorithm. the algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road networks into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and $A^*$ algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3055-3063
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• 2000

In this paper, a task duplication based heuristic scheduling algorithm is proposed to solve the problem of task scheduling on Shared Memory Multiporcessors (SMM). The proposed algorithm pre-allocates network resources so as to avoid potential communication conlhct, and the algorithm uses heuristies to select duplication tasks so as to recuce of a multiprocessors, and generates scheduling accorting to the available number of processors ina system. The proposed algorithm has been applied to some practical task graphs in the simulation, and the results show that the proposed algorithm achieves considerable performance improvement, in respect of schedule length.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.39-46
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• 2009

Generally, Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, we propose an abstract graph for path-finding with dynamic information. The abstract graph is a simple graph as real road network is abstracted. The abstract graph is created by fixed-size cells and real road network. Path-finding with the abstract graph is composed of two step searching, path-finding on the abstract graph and on the real road network. We performed path-finding algorithm with the abstract graph against A* algorithm based on fixed-size cells on road network that consists of 106,254 edges. In result of evaluation of performance, cost of exploring in path-finding with the abstract graph is about 3~30% less than A* algorithm based on fixed-size cells. Quality of path in path-finding with the abstract graph is, However, about 1.5~6.6% more than A* algorithm based on fixed-size cells because edges eliminated are not candidates for path-finding.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.94-98
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• 2000

본 논문은 TFT-LCD 모듈 조립 공정에서의 스케줄링 시스템을 제안한다. TFT-LCD 모듈 조립 공정은 선행 공정인 액정 공정에서 넘어오는 LCD 판넬과 기타 부품들을 조립하여 최종 완제품을 만드는 공정이다. 본 연구에서 다루고 있는 문제는 주문량으로부터 구해지는 일일 생산 계획량이 주어졌을 때 각 라인에서 생산되어질 제품을 배정하는 문제이다. 본 논문의 목적은 주어진 실제 공정 환경에서 일일 생산 계획량을 최대로 만족하기 위한 스케줄링 휴리스틱을 개발하는 것이다. 이를 위해 relaxed LP 모형을 제시하였고 제시된 LP 모형을 이용한 알고리즘을 개발하였다. 제안된 알고리즘은 제품 우선 배정 조건, 현 보유 자재량과 대략적인 라인의 생산 능력을 고려한 LP 프로시져 부분과 제품 간 셋업 시간을 고려한 설비 배정 휴리스틱의 두 부분으로 구분된다. 알고리즘의 성능 검사를 위해 실제 TFT-LCD 모듈 공정에서의 데이터를 이용하여 과거에 실제 이루어진 생산 결과와 비교를 하였으며 제안된 알고리즘의 효율성을 실험 결과를 통해 보였다.