• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.335-341
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• 2000

In this study, the multiobjective linear programming (MOLP) formulation was built to solve for the optimal forest management planning considering carbon sequestration and timber production simultaneously. The formulation was applied to a case study problem to investigate the trends of the optimal forest harvest schedules as the function of preference of forest management for carbon sequestration and timber production. The study site was Mt. Kari area in Hongchun. The formulation includes several site-specific constraints for non-declining yields, upper and lower bounds of cut volume and area for timber, ending inventory conditions, etc.. According to the changes of weight combinations for timber production and carbon sequestration, the joint production possibilities curve was proposed as the option for management choice.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.351-358
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• 2013

This paper proposes a multiobjective model describing the trade-offs involved in selecting the locations of drop-off boxes for collecting used products and transporting these products to designated locations. We assume the following reverse flow of used products. Owners of used products (cellular phones, digital cameras, ink cartridges, etc.) take them to the nearest drop-off box when the distance is reasonably short. We also assume that owners living closer to drop-off boxes dispose of more used products than do owners living farther from drop-off boxes. Different types of used products are collected, with each type requiring its own drop-off box. A transportation destination for each product is specified. Three objectives are considered: maximizing the volume of used products collected at drop-off boxes; minimizing the cost of transporting collected products to designated locations; and minimizing the cost of allocating space for drop-off boxes. We formulate the above model as a multiobjective integer programming problem and generate the corresponding set of Pareto optimal solutions. We apply the model to an area using population data for Chofu City, Tokyo, Japan, and analyze the trade-offs between the objectives.

• Communications of the Korean Mathematical Society
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• v.27 no.2
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• pp.411-423
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• 2012

A nondifferentiable nonlinear semi-infinite programming problem is considered, where the functions involved are ${\eta}$-semidifferentiable type I-preinvex and related functions. Necessary and sufficient optimality conditions are obtained for a nondifferentiable nonlinear semi-in nite programming problem. Also, a Mond-Weir type dual and a general Mond-Weir type dual are formulated for the nondifferentiable semi-infinite programming problem and usual duality results are proved using the concepts of generalized semilocally type I-preinvex and related functions.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.71-74
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• 2014

A new classification framework called 'support feature machine' was introduced in [2] for analyzing medical data. Contrary to authors' claim, however, the proposed method is not designed to guarantee minimizing the use of the spatial feature variables. This paper mathematically remedies this drawback and provides comments on models from [2].

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1079-1085
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• 2007

This Paper Proposes a new optimization algorithm named by GBNSGA-II(Goal-pareto Based Non-dominated Sorting Genetic Algorithm-II) which uses Goal Programming to find non-dominated solutions in NSGA-II. Although the conventional NSGA is very popular to solve multiobjective optimization problem, its high computational complexity, lack of elitism and difficulty of selecting sharing parameter have been considered as problems to be overcome. To overcome these problems, NSGA-II has been introduced as the alternative for multiobjective optimization algorithm preventing aforementioned defects arising in the conventional NSGA. Together with advantageous features of NSGA-II, this paper proposes rather effective optimization algorithm formulated by purposely combining NSGA-II algorithm with GP (Goal Programming) subject to satisfying multiple objectives as possible as it can. By conducting computer simulations, the superiority of the proposed GBNSGA-II algorithm will be verified in the aspects of the effectiveness on optimization process in presence of a priori constrained goals and its fast converging capability.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.621-633
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• 1997

This paper is concerned with the multiobjective vehicle scheduling problem with time and area-dependent travel speeds(MVSPTD), in which two conflicting objectives are explicitly treated and the travel speed between two locations depends on the passing area and time of day. The two objectives are the minimization of total vehicle travel time and the minimization of total weighted tardiness. First, I construct a mixed integer linear programming formulation of the MVSPTD, and present o heuristic algorithm that builds the vehicle schedules based on the savings computed. The results of computational experiments showed that the heuristic performs very well. Finally, I propose an expert system for vehicle scheduling in the MVSPTD. Its whole process is executed under VP-Expert expert system environment.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.41-59
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• 1983

The purpose of this paper is to present a method of multi-objective, stochastic optimization in water resources system which investigates the development of potential non-normal deterministic equivalents for subsequent use in multiobjective stochastic programming methods, Given probability statement involving a function of several random variables, it is often possible to obtain a deterministic equivalent of it that does not include any orginal random variables. A Stochastic trade-off technique-MSTOT is suggested to help a decision maker achieve satisfactory levels for several objective functions. This makes use of deterministic equivalents to handle random variables in the objective functions. The emphasis is in the development of non-normal deterministic equivalents for use in multiobjective stochastic techniques.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.161-172
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• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.161-172
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• 1996

Although conventional computer programs use efficient and precise optimization algorithms, they can not emulate the problem solving capabilities of human experts. A design optimization process involves a number of tasks which require human expertise and experience. Traditional optimization systems have concentrated on numerical aspects of a design process and have not been successful in integrating the numerical parts with human expertise. On the other hand, most knowledge-based systems focus on symbolic reasoning and have been little concerned with the numerical processes. The objective of this paper is to develop a knowledge-based multiobjective optimum design system which has the capabilities of knowledge processing and numerical computation by integrating the multiobjective optimization method and the knowledge-based system. The knowledge-based system for symbolic processing is developed. Rules for knowledge representation and the inference mechanism of the system are written in LISP. The knowledge-based multiobjective optimum design system is finally developed by integrating the multiobjective optimization method and the knowledge-based system by applying shell programming technique. The system is applied to an optimum design model of a LNG carrier in the preliminary design stage. It is found that the system well simulate design variables and objective functions of the design model.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.589-605
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• 1996

Recycling of used products and components has been considered as one of promising strategies for resolving environmental problems. In this respect, most manufacturing companies begin to consider possible recycling (e.q., reuse or re-production) of the components contained in their products. The primary objective of this research is to develop a multiple criteria decision making model for systematic management of recycle-oriented manufacturing components. The production planning problem of recycle-oriented manufacturing components is first formulated as a multiobjective mixed 0-1 integer programming model with three conflicting objectives. An interactive multiple criteria decision making method is then developed for solving the mathematical model. Also, an Input/Output analysis software is developed to help practitioners apply the model to real problems without much knowledge on computers and mathematical programming. A numerical example is used in examining the validity of the proposed model and to investigate the impact of the input variables on recycling production strategy.