• 제목/요약/키워드: Genetic Approach

검색결과 1,327건 처리시간 0.025초

최적화의 효율향상을 위한 유전해법과 직접탐색법의 혼용에 관한 연구 (A Study on Hybrid Approach for Improvement of Optimization Efficiency using a Genetic Algorithm and a Local Minimization Algorithm)

  • 이동곤;김수영;이창억
    • 산업공학
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    • 제8권1호
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    • pp.23-30
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    • 1995
  • Optimization in the engineering design is to select the best of many possible design alternatives in a complex design space. One major problem of local minimization algorithm is that they often result in local optima. In this paper, a hybrid method was developed by coupling the genetic algorithm and a traditional direct search method. The proposed method first finds a region for possible global optimum using the genetic algorithm and then searchs for a global optimum using the direct search method. To evaluate the performance of the hybrid method, it was applied to three test problems and a problem of designing corrugate bulkhead of a ship.

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유전자 알고리즘을 이용한 전력조류계산의 새로운 접근 (A New Approach for the Power Flow Solution Using Genetic-based Optimization)

  • 장승찬;김정훈;이봉용
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.494-496
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    • 1995
  • This paper presents a methodology of improving a conventional numerical model in power systems using GAs and a new GAs-based model which can directly solve the real-valued optimum in the optimization procedure. The power flow which is well known to the power engineer is solved using the proposed GAs as an alternative way of the traditional optimization method. In applying GAs to the power flow, both the notions on a way of the genetic representations and a realization of the genetic operators are fully discussed to evaluate the GA's effectiveness.

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GENIIS, a New Hybrid Algorithm for Solving the Mixed Chinese Postman Problem

  • 최명길;응우엔만탕;황원주
    • 한국정보시스템학회지:정보시스템연구
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    • 제17권3호
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    • pp.39-58
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    • 2008
  • Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.

유전 알고리듬을 이용한 U형태 혼합모델에서의 작업시간과 육체적 작업부하를 고려한 최적 라인밸런싱 (A U-shape Mixed Model Assembly Line Balancing Problem for Processing Time and Physical Workload Using the Genetic Algorithm)

  • 최경현;김찬우
    • 산업경영시스템학회지
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    • 제28권3호
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    • pp.98-108
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    • 2005
  • The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U-shape mixed-model assembly line balancing and considers both the processing time and the physical workloads. We suggest the goal programming approach for this situation and to overcome some difficulties of finding optimal solution, we adopt the genetic algorithm that is one of the most promising solution techniques. We tested several test problems and present the results that indicate some improvement for the line balancing as well as the stable performance of the algorithm.

대화형 진화 연산을 이용한 아바타 생성 (An Interactive Approach based on Genetic Algorithm Using Hidden Population and Simplified Genotype for Avatar Synthesis)

  • 이자용;백일현;강훈
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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    • pp.482-487
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    • 2002
  • 본 논문에서는 사용자 개개인에 최적화된 아바타를 생성하기 위해 대화형 진화 연산(Interactive Genetic Algorithm, IGA)을 적용하는 방법을 제안하고 있다. IGA는 사용자의 선택을 적합도 평가에 사용하는 방법이기 때문에, 사용자의 개인적인 취향을 아바타 생성 과정에 반영할 수 있다. 본 연구에서는 기존의 IGA가 가지고 있는 단점을 극복하기 위해 'hidden population' , 'primitive avatar' , 'simplified genotype' 기법을 제안한다. 이러한 방법들은 단시간 내에 최적화된 결과물을 생성하도록 유도함으로써 IGA 시스템의 최대 문제점인 사용자의 피로도를 최소화한다. 마지막으로, 제안하고 있는 알고리즘의 우수성을 증명하기 위해 사용자의 만족도나 신뢰도를 측정할 수 있는 독자적인 평가 방법을 소개하고 있다.

Evolutionary Design for Multi-domain Engineering System - Air Pump Redesign

  • 서기성
    • 한국지능시스템학회논문지
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    • 제16권2호
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    • pp.228-233
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    • 2006
  • This paper introduces design method for air pump system using bond graph and genetic programming to maximize outflow subject to a constraint specifying maximum power consumption. The air pump system is a mixed domain system which includes electromagnetic, mechanical and pneumatic elements. Therefore an appropriate approach for a better system for synthesis is required. Bond graphs are domain independent, allow free composition, and are efficient for classification and analysis of models. Genetic programming is well recognized as a powerful tool for open-ended search. The combination of these two powerful methods, BG/GP, was tested for redesign of air pump system.

대체 공정을 도입한 유전 알고리즘 응용의 작업 일정 계획 (A Genetic Algorithm Approach to Job Shop Scheduling Considering Alternative Process Plans)

  • 박지형;최회련;김영휘
    • 대한산업공학회지
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    • 제24권4호
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    • pp.551-558
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    • 1998
  • In this paper, a job shop scheduling system is developed which can cope with the changes of shop floor status with flexibility. This system suggests near optimal sequence of operations by using Genetic Algorithm which considers alternative process plans. The Genetic Algorithm proposed in this paper has some characteristics. The mutation rate is differentiated in order to enhance the chance to escape a local optimum and to assure the global optimum. And it employs the double gene structure to easily make the modeling of the shop floor. Finally, the quality of its solution and the computational time are examined in comparison with the method of a Simulated Annealing.

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Constructing Container Shipping Networks with Empty Container Repositioning among Calling Ports - a Genetic Algorithm Approach

  • Shintani, Koichi;Imai, Akio;Nishmura, Etsuko;Papadimitriou, Stratos
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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    • pp.157-164
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    • 2006
  • This paper addresses the design of container liner shipping service networks by explicitly taking into account empty container repositioning and container fleet size. Two key and interrelated issues of deployments of ships and containers are usually treated separately by most existing studies on shipping network design. In this paper, both issues are considered simultaneously. The problem is formulated as a two-stage problem: the upper-problem being formulated as a Knapsack problem and the lower-problem as a Flow problem. A genetic algorithm based heuristic is developed for the problem. Through a number of numerical experiments that were conducted it was shown that the problem considering empty container repositioning provides a more insightful solution than the one without.

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A Numerical Experiment in Assimilating Agricultural Practices in a Mixed Pixel Environment using Genetic Algorithms

  • Honda, Kyoshi;Ines, Amor V.M.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.837-839
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    • 2003
  • Low spatial resolution remote sensing (RS) data (LSRD) are promising in agricultural monitoring activities due to their high temporal resolution, but under such a spatial resolution, mixing in a pixel is a common problem. In this study, a numerical experiment was conducted to explore a mixed pixel problem in agriculture using a combined RSsimulation model SWAP (Soil-Water-Atmosphere -Plant) and a Genetic Algorithm (GA) approach. Results of the experiments showed that it is highly possible to address the mixed pixel problem with LSRD.

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Stabilization of Inverted Pendulum Using Neural Network with Genetic Algorithm

  • 김단;김갑일;손영익
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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    • pp.425-428
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    • 2003
  • In this paper, the stabilization of an inverted pendulum system is studied. Here, the PID control method is adopted to make the system stable. In order to adjust the PID gains, a three-layer neural network, which is based on the back propagation method, is used. Meanwhile, the time for training the neural network depends on the initial values of PID gains and connection weights. Hence, the genetic algorithm Is considered to shorten the time to find the desired values. Simulation results show the effectiveness of the proposed approach.

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