• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.93.3-93
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• 2002

$\textbullet$ Co-evolutionary algorithms $\textbullet$ Nash Genetic Algorithms $\textbullet$ Multi-objective Optimization $\textbullet$ Distance dependent mutation $\textbullet$ Pareto Optimality

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.279-286
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• 2005

The objective of this study is to suggest a credit scoring model of a capital company's customers by integration of multiple classifiers using genetic algorithm. For this purpose , an integrated model is derived in two phases. In first phase, three types of classifiers MLP (Multi-Layered Perceptron), RBF (Radial Basis Function) and linear models - are trained, in which each type has three ones respectively so htat we have nine classifiers totally. In second phase, genetic algorithm is applied twice for integration of classifiers. That is, after htree models are derived from each group, a final one is from these three, In result, our suggested model shows a superior accuracy to any single ones.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.209-216
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• 2005

The controller that can control the smart base isolation system consisting of M damper and friction pendulum systems(FPS) is developed in this study. A fuzzy logic controller (FLC) is used to modulate the M damper force because the FLC has an inherent robustness and ability to handle non-linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. When earthquake excitations are applied to the structures equipped with smart base isolation system, the relative displacement at the isolation level as well as the acceleration of the structure should be regulated under appropriate level. Thus, NSGA-II(Non-dominated Sorting Genetic Algorithm) is employed in this study as a multi-objective genetic algorithm to meet more than two control objectives, simultaneously. NSGA-II is used to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can efficiently find Pareto optimal sets that can reduce both structural acceleration and base drift from numerical studies.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.203-208
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• 2002

In case of the problems with multiple plants, alternative operation sequence, alternative machine, setup time, and transportation time between plants, we need a robust methodology for the integration of process planning and scheduling in supply chain. The objective of this model is to minimize the tardiness and to maximize the resource utilization. So, we propose a multi-objective model with limited-capacity constraint. To solve this model, we develope an efficient and flexible model using adaptive genetic algorithm(AGA), compared to traditional genetic algorithm(TGA)

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.916-918
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• 2005

다목적 최적화 문제의 목표는 다양한 파레토 최적해(Pareto Optimal Solution)을 찾는데 있으며, 마이크로-유전자 알고리즘(Micro-Genetic Algorithm)은 단순 유전자 알고리즘(Simple Genetic Algorithm)에 비해 소수의 유전자들만을 선별하여 진화시키는 방식으로 효율성을 극대화시킨다. 본 논문에서는 다양한 목적을 동시에 최적화하는 다목적 멀티캐스트 라우팅 문제를 해결하기 위해서 다목적 유전자 알고리즘과 마이크로-유전자 알고리즘을 결합한 다목적 마이크로-유전자 알고리즘을 적용하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.829-836
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• 2002

The paper presents a multi-objective genetic algorithm approach to the design of a water distribution network. The objectives considered are minimization of network cost and maximization of a reliability measure. In this study, a new reliability measure, called network resilience, is introduced. This measure mimics a designer's desire of providing excess power at nodes and designing reliable loops with practicable pipe diameters. The proposed method produces a set of Pareto-optimal solutions in the search space of cost and network resilience. Genetic algorithms are observed to be poor in handling constraints. To handle constraints in a better way, a constraint handling technique that does not require a penalty coefficient and applicable to water distribution systems is presented. The present model is applied to two example problems, which were widely reported. Pipe failure analysis carried out on some of the solutions obtained revealed that the network resilience based approach gave better results in terms of network reliability.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.170-175
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• 2001

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multiple objective genetic algorithm (MOGA), and a sample test case is presented to show the effects of optimizing the sequence with MOGA.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.