• Title/Summary/Keyword: optimization problem

검색결과 4,333건 처리시간 0.027초

Optimization of Fuzzy Car Controller Using Genetic Algorithm

  • Kim, Bong-Gi;Song, Jin-Kook;Shin, Chang-Doon
    • Journal of information and communication convergence engineering
    • /
    • 제6권2호
    • /
    • pp.222-227
    • /
    • 2008
  • The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

최적화 문제 해결 기법 연구 (Resolutions of NP-complete Optimization Problem)

  • 김동윤;김상희;고보연
    • 한국국방경영분석학회지
    • /
    • 제17권1호
    • /
    • pp.146-158
    • /
    • 1991
  • In this paper, we deal with the TSP (Traveling Salesperson Problem) which is well-known as NP-complete optimization problem. the TSP is applicable to network routing. task allocation or scheduling. and VLSI wiring. Well known numerical methods such as Newton's Metheod. Gradient Method, Simplex Method can not be applicable to find Global Solution but the just give Local Minimum. Exhaustive search over all cyclic paths requires 1/2 (n-1) ! paths, so there is no computer to solve more than 15-cities. Heuristic algorithm. Simulated Annealing, Artificial Neural Net method can be used to get reasonable near-optimum with polynomial execution time on problem size. Therefore, we are able to select the fittest one according to the environment of problem domain. Three methods are simulated about symmetric TSP with 30 and 50-city samples and are compared by means of the quality of solution and the running time.

  • PDF

SOLVING OF SECOND ORDER NONLINEAR PDE PROBLEMS BY USING ARTIFICIAL CONTROLS WITH CONTROLLED ERROR

  • Gachpazan, M.;Kamyad, A.V.
    • Journal of applied mathematics & informatics
    • /
    • 제15권1_2호
    • /
    • pp.173-184
    • /
    • 2004
  • In this paper, we find the approximate solution of a second order nonlinear partial differential equation on a simple connected region in $R^2$. We transfer this problem to a new problem of second order nonlinear partial differential equation on a rectangle. Then, we transformed the later one to an equivalent optimization problem. Then we consider the optimization problem as a distributed parameter system with artificial controls. Finally, by using the theory of measure, we obtain the approximate solution of the original problem. In this paper also the global error in $L_1$ is controlled.

Optimal shape design of a polymer extrusion die by inverse formulation

  • Na, Su-Yeon;Lee, Tai-Yong
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
    • /
    • pp.315-318
    • /
    • 1995
  • The optimum design problem of a coat-hanger die is solved by the inverse formulation. The flow in the die is analyzed using three-dimensional model. The new model for the manifold geometry is developed for the inverse formulation. The inverse problem for the optimum die geometry is formed as the optimization problem whose objective function is the linear combination of the square sum of pressure gradient deviation at die exit and the penalty function relating to the measure of non-smoothness of solution. From the several iterative solutions of the optimization problem, the optimum solution can be obtained automatically while producing the uniform flow rate distribution at die exit.

  • PDF

신경회로망을 이용한 직사각형의 최적배치에 관한 연구 (A Study on Optimal Layout of Two-Dimensional Rectangular Shapes Using Neural Network)

  • 한국찬;나석주
    • 대한기계학회논문집
    • /
    • 제17권12호
    • /
    • pp.3063-3072
    • /
    • 1993
  • The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.

멀티캐스트 라우팅을 위한 다목적 마이크로-유전자 알고리즘 (Multi-Objective Micro-Genetic Algorithm for Multicast Routing)

  • 전성화;한치근
    • 산업공학
    • /
    • 제20권4호
    • /
    • pp.504-514
    • /
    • 2007
  • The multicast routing problem lies in the composition of a multicast routing tree including a source node and multiple destinations. There is a trade-off relationship between cost and delay, and the multicast routing problem of optimizing these two conditions at the same time is a difficult problem to solve and it belongs to a multi-objective optimization problem (MOOP). A multi-objective genetic algorithm (MOGA) is efficient to solve MOOP. A micro-genetic algorithm(${\mu}GA$) is a genetic algorithm with a very small population and a reinitialization process, and it is faster than a simple genetic algorithm (SGA). We propose a multi-objective micro-genetic algorithm (MO${\mu}GA$) that combines a MOGA and a ${\mu}GA$ to find optimal solutions (Pareto optimal solutions) of multicast routing problems. Computational results of a MO${\mu}GA$ show fast convergence and give better solutions for the same amount of computation than a MOGA.

용량제약이 있는 복수 순회구매자 문제의 휴리스틱 해법 (Heuristic Approach for the Capacitated Multiple Traveling Purchaser Problem)

  • 최명진;이상헌
    • 산업공학
    • /
    • 제24권1호
    • /
    • pp.51-57
    • /
    • 2011
  • The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In the last decade, TPP has received some attention of the researchers in the operational research area. However, all of the past researches for TPP are restricted on a single purchaser (vehicle). It could be the limitation to solve the real world problem. The purpose of this paper is to suggest the capacitated multiple TPP (CMTPP). It could be used in inbound logistics optimization in supply chain management area and many others. Since TPP is known as NP-hard, we also developed the heuristic algorithm to solve the CMTPP.

포병화력 생존성지원을 위한 진지구축경로문제 연구 (Study on Vehicle Routing Problem of Artillery Position Construction for Survivability Support)

  • 문정현;이상헌
    • 대한산업공학회지
    • /
    • 제37권3호
    • /
    • pp.171-179
    • /
    • 2011
  • In this paper, we deal with the vehicle routing problem that could establish operational plan of military engineer for survivability support of artillery position construction. We propose VRPTW(vehicle routing problem with time-window) model of special form that considered service level to reflect the characteristics of military operations rather than the logic of economic efficiencies in the objective function. Furthermore we suggest modified particle swarm optimization algorithm for service based vehicle routing problem solution that can be possible to search in complicated and uncertain area and control relation softly between global and local search.

다개체 로봇 편대 제어를 위한 이동 구간 입자 군집 최적화 알고리즘의 통계적 성능 분석 (Statistical Analysis of Receding Horizon Particle Swarm Optimization for Multi-Robot Formation Control)

  • 이승목
    • 한국산업정보학회논문지
    • /
    • 제24권5호
    • /
    • pp.115-120
    • /
    • 2019
  • 본 논문에서는 이동 구간 입자 군집 최적화 (Receding horizon particle swarm optimization; RHPSO) 알고리즘 기반 다개체 로봇 편대 제어 알고리즘의 통계적 성능 분석 결과를 제시한다. 다개체 로봇의 편대 제어 문제는 로봇 간 충돌 회피를 고려할 경우, 구속 조건이 있는 비선형 최적화 문제로 정의될 수 있다. 일반적으로 구속 조건이 있는 비선형 최적화 문제는 최적해를 찾는데 많은 시간이 걸리는 문제점이 있다. 이동 구간 입자 군집 최적화 알고리즘은 로봇 편대 제어의 최적화 문제에 대한 준최적해를 빠르게 찾기 위해 제안된 알고리즘이다. 이동 구간 입자 군집 최적화 알고리즘은 알고리즘에 사용되는 후보해의 개수와 세대 수가 증가함에 따라 계산 복잡도가 증가한다. 따라서 최소의 후보해와 세대 수만으로 실시간 제어에 사용될 수 있는 준최적해를 찾는 것이 중요하다. 본 논문에서는 이동 구간 입자 군집 최적화 알고리즘의 후보해의 수와 세대 수에 따른 제어 오차를 비교하였다. 다양한 조건의 시뮬레이션 실험을 통해서 통계적으로 결과를 분석하고, 허용 가능한 편대 오차 범위 내에서 이동 구간 입자 군집 최적화 알고리즘의 최소 후보해의 수와 세대 수를 도출한다.

트러스 구조물의 형상최적화에 관한 연구 (The configuration Optimization of Truss Structure)

  • 임연수;최병한;이규원
    • 한국강구조학회 논문집
    • /
    • 제16권1호통권68호
    • /
    • pp.123-134
    • /
    • 2004
  • 본 연구에서는 효율적인 형상최적화를 위해 다단계 분할기법으로 트러스 구조물의 형상 최적화를 시도하였다. 1단계에서는 단면적을 설계변수로 하여 중량, 또는 체적을 목적함수로 하고 다하중 재하조건 하의 거동제약조건과 부가적인 제약조건을 고려하여 비선형 최적화 문제를 형성한다. 이 비선형 계획문제를 축차 선형계획 문제로 변환하여 개선된 허용방향법으로 최적화하였다. 이때 필요한 도함수는 다른 연구와 달리 효율적이라고 알려진 거동공간법으로 구하였고, 최적화 과정 중 이를 이용하여 부재력를 근사화 함으로써 계산의 효율성을 높였다. 2단계에서는 형상 설계변수만을 고려한 무제약 최적화 문제로 형성한 후 일방향 탐사기법을 적용하여 형상을 최적화하였다. 이와 같이 구성된 본 연구의 알고리즘을 몇 가지 트러스 구조물에 적용하여 본 알고리즘의 적용성과 효율성 및 타당성을 증명하였다.