• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.463-474
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• 2004

Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

• 한국구조물진단유지관리공학회 논문집
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• 제24권3호
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• pp.26-38
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• 2020

자기 충전형 콘크리트의 배합물 설계는 전형적인 다기준의사결정의 과정이다. 본 연구에서는 실험설계법과 반응표면법을 이용하여 SCC 배합물 전산 설계가 가능하도록 재료성능 및 비용모델을 생성하고, 요구조건을 반영한 여러 성능 사이의 상대적 중요도를 산정하여 가중 다목적 설계문제로 정식화하여 수치최적해를 계산함으로써 비용효율을 고려한 SCC최적설계를 수행하였다. 실험비용과 시간을 고려하여 SCC의 수많은 요구성능 중 압축강도, 철근충전성, 재료분리저항성, 비용정보 등을 다목적 최적화의 목적함수로 설정하였다. 재료경제성을 최적재료설계프로세스에 합리적으로 반영함으로써 경제적 콘크리트배합설계를 수행할 수 있었으며, 본 연구 결과 실험점 계획에서부터 최적해 산출에 이르는 과정을 객관적인 프로세스로 구성함으로써 콘크리트 범용 최적재료설계기술 및 전산화를 기대할 수 있다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.