• 제목/요약/키워드: solution algorithm

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수정 유전자 알고리듬을 이용한 중복방문, 다중차고 차량경로문제 (A Vehicle Routing Problem with Double-Trip and Multiple Depots by using Modified Genetic Algorithm)

  • 전건욱;심재영
    • 산업공학
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    • 제17권spc호
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    • pp.28-36
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    • 2004
  • The main purpose of this study is to find out the optimal solution of the vehicle routing problem considering heterogeneous vehicle(s), double-trips, and multi depots. This study suggests a mathematical programming model with new numerical formula which considers the amount of delivery and sub-tour elimination and gives optimal solution by using OPL-STUDIO(ILOG). This study also suggests modified genetic algorithm which considers the improvement of the creation method for initial solution, application of demanding point, individual and last learning method in order to find excellent solution, survival probability of infeasible solution for allowance, and floating mutation rate for escaping from local solution. The suggested modified genetic algorithm is compared with optimal solution of the existing problems. We found the better solution rather than the existing genetic algorithm. The suggested modified genetic algorithm is tested by Eilon and Fisher data(Eilon 22, Eilon 23, Eilon 30, Eilon 33, and Fisher 10), respectively.

이산공간에서 순차적 알고리듬(SOA)을 이용한 전역최적화 (Global Optimization Using a Sequential Algorithm with Orthogonal Arrays in Discrete Space)

  • 조범상;이정욱;박경진
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 추계학술대회
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    • pp.858-863
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    • 2004
  • In the optimized design of an actual structure, the design variable should be selected among any certain values or corresponds to a discrete design variable that needs to handle the size of a pre-formatted part. Various algorithms have been developed for discrete design. As recently reported, the sequential algorithm with orthogonal arrays(SOA), which is a local minimum search algorithm in discrete space, has excellent local minimum search ability. It reduces the number of function evaluation using orthogonal arrays. However it only finds a local minimum and the final solution depends on the initial value. In this research, the genetic algorithm, which defines an initial population with the potential solution in a global space, is adopted in SOA. The new algorithm, sequential algorithm with orthogonal arrays and genetic algorithm(SOAGA), can find a global solution with the properties of genetic algorithm and the solution is found rapidly with the characteristics of SOA.

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Genetic Algorithm을 이용한 다중 프로세서 일정계획문제의 효울적 해법 (An Efficient Method for Multiprocessor Scheduling Problem Using Genetic Algorithm)

  • 박승헌;오용주
    • 한국경영과학회지
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    • 제21권1호
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    • pp.147-161
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    • 1996
  • Generally the Multiprocessor Scheduling (MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm (GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and GP/MISF (Critical Path/Most Immediate Successors First). An efficient genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with GA to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

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Genetic algorithm을 이용한 다중 프로세서 일정계획문제의 효율적 해법 (An efficient method for multiprocessor scheduling problem using genetic algorithm)

  • 오용주;박승헌
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1995년도 추계학술대회발표논문집; 서울대학교, 서울; 30 Sep. 1995
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    • pp.220-229
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    • 1995
  • Generally the Multiprocessor Scheduling(MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm(GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and CP/MISF(Critical Path/Most Immediate Successors First). A new genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with Ga to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

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차량 경로 문제의 발견적 해법 (A Heuristic Algorithm for the Vehicle Routing Problem)

  • 정영민;민계료
    • 한국국방경영분석학회지
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    • 제26권1호
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    • pp.47-55
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    • 2000
  • The purpose of this paper is to develop a new heuristic algorithm for vehicle routing problem. The algorithm is composed of two steps. First step is to make a initial solution using sweeping algorithm. Second step is to improve initial solution for optimal solution using node exchange algorithm and tabu search algorithm. We have proven that our algorithm has produced better results than solutions obtained by saving algorithm and genetic in ten example problems with different unit size.

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할당 문제의 최적 알고리즘 (The Optimal Algorithm for Assignment Problem)

  • 이상운
    • 한국컴퓨터정보학회논문지
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    • 제17권9호
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    • pp.139-147
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    • 2012
  • 본 논문에서는 할당 문제의 최적해를 간단히 찾을 수 있는 알고리즘을 제안하였다. 일반적으로 할당 문제의 최적해는 Hungarian 알고리즘으로 구한다. 제안된 알고리즘은 Hungarian 알고리즘의 4단계 수행 과정을 1단계로 단축시켰으며, 행과 열의 최소 비용만을 선택하여 비용을 감소시키는 최적화 과정을 거쳐 최적해를 구하였다. 제안된 알고리즘을 27개의 균형 할당 문제와 7개의 불균형 할당 문제에 적용한 결과 유전자 알고리즘으로 찾지 못한 최적해를 찾는데 성공하였다. 제안된 알고리즘은 Hungarian 알고리즘의 수행 복잡도 O($n^3$)을 O(n)으로 향상시켰다. 따라서 제안된 알고리즘은 Hungarian 알고리즘을 대체하여 할당 문제에 일반적으로 적용할 수 있는 알고리즘으로 널리 활용될 수 있을 것이다.

GPS 관측치 위치계산을 위한 부동점 알고리즘 (Fixed Point Algorithm for GPS Measurement Solution)

  • 임삼성
    • 한국항행학회논문지
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    • 제4권1호
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    • pp.45-49
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    • 2000
  • GPS에 의한 관측치는 시각오차, 전리층과 대류층 지연오차, 다중경로 오차와 같은 다양한 오차를 내포하고 있어서 GPS 관측치 위치계산시 일반적으로 최소자승해를 구하게 된다. GPS 관측치는 비선형 방정식을 만족하므로 최소자승해를 구하기 위해서는 비선형 Newton 알고리즘을 이용할 수도 있으나 대개 간편성과 효율성 때문에 선형화 알고리즘을 적용하게 된다. 본 연구에서는 비선형 Newton 알고리즘이나 선형화 알고리즘을 대체할 수 있는 부동점 알고리즘을 개발하여 그 유용성을 증명하였다. 비선형 Newton 알고리즘이나 선형화 알고리즘은 수렴속도가 빠른 장점을 가지고 있으나 초기값이 해와 근사하여야 한다는 단점이 있다. 반면 부동점 알고리즘은 수령속도는 다소 느리나 초기값이 대단히 부정확하여도 수렴가능한 장점이 있으므로 두 알고리즘을 적절히 혼용하는 것이 좋을 것이다.

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병렬라인 검사공정의 작업배분을 위한 휴리스틱 알고리즘의 성능 개선 (Performance improvement of heuristic algorithm to assign job in parallel line inspection process)

  • 박승헌;이석환
    • 대한안전경영과학회지
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    • 제14권1호
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    • pp.167-177
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    • 2012
  • In this paper, we raised the performance of heuristic algorithm to assign job to workers in parallel line inspection process without sequence. In previous research, we developed the heuristic algorithm. But the heuristic algorithm can't find optimal solution perfectly. In order to solve this problem, we proposed new method to make initial solution called FN(First Next) method and combined the new FN method and old FE method using previous heuristic algorithm. Experiments of assigning job are performed to evaluate performance of this FE+FN heuristic algorithm. The result shows that the FE+FN heuristic algorithm can find the optimal solution to assign job to workers evenly in many type of cases. Especially, in case there are optimal solutions, this heuristic algorithm can find the optimal solution perfectly.

An Linear Bottleneck Assignment Problem (LBAP) Algorithm Using the Improving Method of Solution for Linear Minsum Assignment Problem (LSAP)

  • Lee, Sang-Un
    • 한국컴퓨터정보학회논문지
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    • 제21권1호
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    • pp.131-138
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    • 2016
  • In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

경로기반 해법알고리즘을 이용한 동적통행배분모형의 개발 (A ROUTE-BASED SOLUTION ALGORITHM FOR DYNAMIC USER EQUILIBRIUM ASSIGNMENT)

  • Sangjin Han
    • 대한교통학회:학술대회논문집
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    • 대한교통학회 2002년도 제41회 학술발표회논문집
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    • pp.97-139
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    • 2002
  • The aim of the present study is to find a good quality user equilibrium assignments under time varying condition. For this purpose, this study introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it develops a novel solution algorithm that does not need evaluation of the objective function by modifying the Schittenhelm (1990)'s algorithm. This novel algorithm turns out to be efficient and convenient compared to the conventional Frank-Wolfe (1956) algorithm because the former finds solutions based on routes rather than links so that it can maintain correct flow propagation intrinsically in the time-varying network conditions. The application of dynamic user equilibrium (DUE) assignment model with this novel solution algorithm to test networks including medium-sized one shows that the present DUE assignment model gives rise to high quality discrete time solutions when we adopt the deterministic queuing model for a link performance function, and we associate flows and costs in a proper way.

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