• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.220-227
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• 2018

The cooperative game theory consists of a set of players and utility function that has positive values for a subset of players, called coalition, in the game. The purpose of cost allocation method is to allocate the relevant cost among game players in a fair and rational way. Therefore, cost allocation method based on cooperative game theory has been applied in many areas for fair and reasonable cost allocation. On the other hand, the desirable characteristics of the cost allocation method are Pareto optimality, rationality, and marginality. Pareto optimality means that costs are entirely paid by participating players. Rationality means that by joining the grand coalition, players do not pay more than they would if they chose to be part of any smaller coalition of players. Marginality means that players are charged at least enough to cover their marginal costs. If these characteristics are all met, the solution of cost allocation method exists in the core. In this study, proportional method is applied to EOQ inventory game and EPQ inventory game with shortage. Proportional method is a method that allocates costs proportionally to a certain allocator. This method has been applied to a variety of problems because of its convenience and simple calculations. However, depending on what the allocator is used for, the proportional method has a weakness that its solution may not exist in the core. Three allocators such as demand, marginal cost, and cost are considered. We prove that the solution of the proportional method to demand and the proportional method to marginal cost for EOQ game and EPQ game with shortage is in the core. The counterexample also shows that the solution of the proportional method to cost does not exist in the core.

• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.222-228
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• 2010

In this paper, we propose a optimization approach for the Electric Locomotive Overhaul Maintenance Facility (ELOMF), which aims at the simulation optimization so as to meet the design specification. In simulation design, we consider the critical path and sensitivity analysis of the critical (dependent) factors and the design (independent) parameters for the parameter selection and reduction of the metamodel. Therefore, we construct the multi-objective non-linear programming. The objective function is normalized for the generalization of design parameter while the constraints are composed of the simulation-based regression metamodel for the critical factors and design factor's domain. Then the effective solution procedure based on the pareto optimal solution set is proposed. This approach provides a comprehensive approach for the optimization of Train Overhaul Maintenance Facility(TOMF)'s design parameters using the simulation and metamoels.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.45-54
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• 2007

In this article, we propose a different modeling approach, which aims at the simulation optimization so as to meet the design specification. Generally, Multi objective optimization problem is formulated by dependent factors as objective functions and independent factors as constraints. However, this paper presents the critical(dependent) factors as objective function and design(independent) factors as constraints for the selection of design factors directly. The objective function is normalized far the generalization of design factors while the constraints are composed of the simulation-based regression metamodels fer the critical factors and design factor's domain. Then the effective and fast solution procedure based on the pareto optimal solution set is proposed. This paper provides a comprehensive framework for the system design using the simulation and metamodels. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situations.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.93-102
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• 2009

A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

• The Journal of Fisheries Business Administration
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• v.42 no.3
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• pp.31-39
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• 2011

This paper attempts to extend such analysis to the rather more difficult problem of optimal management of transnational fish stocks jointly owned by two countries. Transboundary fish such as Mackerel creates an incentive to harvest fish before a competitor does and leads to over-exploitation. This tendency is especially poignant for transnational stocks since, in the absence of an enforceable, international agreement, there is little or no reason for either government or the fishing industry to promote resource conservation and economic efficiency. In the current paper I examine a game theoretic setting in which cooperative management can provide more benefits than noncooperative management. A dynamic model of Mackerel fishery is combined with Nash's theory of two countries cooperative games. A characteristic function game approach is applied to describe the sharing of the surplus benefits from cooperation and noncooperation. A bioeconomic model was used to compare the economic yield of the optimal strategies for two countries, under joint maximization of net benefits in joint ocean. The results suggest as follows. First, the threat points represent the net benefits for two countries in absence of cooperation. The net benefits to Korea and China in threat points are 2,000 billion won(${\pi}^0_{KO}$) and 1,130 billion won(${\pi}^0_{CH}$). Total benefits are 3,130 billion won. Second, if two countries cooperate one with another, they reach the solution payoffs such as Pareto efficient. The net benefits to Korea and China in Pareto efficient are 2,785 billion won(${\pi}^0_{KO}$) and 1,605 billion won(${\pi}^0_{CH}$) or total benefits of 4,390 billion won : a gain of 1,260 billion won. Third, the different price effects under the two scenarios show that total benefit rise as price increases.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.23-35
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• 2023

In this study, we developed a method to determine the flood-limited water levels of agricultural reservoirs, considering both their irrigation and flood control functions. Irrigation safety and flood safety indices were defined to be applied to various reservoirs, allowing for a comprehensive assessment of the irrigation and flood control properties. Seasonal flood-limited water level scenarios were established to represent the temporal characteristics of rainfall and agricultural water supply and the safety indices were analyzed according to these scenarios. The optimal scenarios were derived using a schematic solution based on Pareto front analysis. The method was applied to Obong, Yedang, and Myogok reservoirs, and the results showed that the characteristics of each reservoir were well represented in the safety indices. The irrigation safety of Obong reservoir was found to be significantly influenced by the late-stage flood-limited water level, while those of Yedang and Myogok reservoir were primarily affected by the early and mid-stage flood-limited water levels. The values of irrigation safety and flood safety indices for each scenario were plotted as points on the coordinate plane, and the optimal flood-limited water levels were selected from the Pareto front. The storage ratio of the optimal flood-limited water levels for the early, mid, and late stages were 65-70%, 70%, and 75% for Obong reservoir, 75%, 70-75%, and 65-70% for Yedang reservoir, and 75-80%, 70%, and 50% for Myogok reservoir. We expect that the method developed in this study will facilitate efficient reservoir operations.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.77-80
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• 1998

An optimization procedure was proposed to minimize construction and operation cost simultaneously. The global criterion method was exploited to find a Pareto optimum solution to the multi-objective functions. The result was compared to the data of a real pumping plant and it was found that the optimized plan of pumping plant could reduce both of the construction and operation cost.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.511-513
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• 2003

멀티미디어 서비스의 증가로 다양한 QoS(Quality of Service) 파라미터를 보장하는 멀티캐스트 라우팅 알고리즘이 필요하게 되었다. 이러한 멀티캐스트 라우팅에서 고려해야 하는 각각의 QoS 파리미터와 비용과의 관계는 Trade-off 관계에 있으며, 이들을 동시에 최적화하는 멀티캐스트 라우팅 문제는 다목적 최적화 문제(Multi-Objective Optimization Problem: MOOP)에 속하는 어려운 문제이다. 다목적 최적화 문제의 목표는 다양한 파레토 최적해(Pareto Optimal Solution)를 찾는데 있으며, 이를 해결하기 위해서 본 논문에서는 다목적 유전자 알고리즘(Multiple Objective Genetic Algorithms： MOGA)을 적용하였다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1353-1355
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• 2003

Genetic algorithms (GA) is a well known technique that is capable of handling multiobjective functions and discrete constraints in the process of numerical optimization. Together with the Pareto ranking scheme, more than one possible solution can be obtained despite the imposed constraints and multi-criteria design functions. In view of this unique capability, the design of the log-periodic dipole antenna array (LPDA) using this special feature is proposed in this paper. This method also provides gain, front-back level and S parameter design tradeoff for the LPDA design in broadband application at no extra computational cost.