• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• IE interfaces
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• v.15 no.1
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• pp.49-54
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• 2002

A bus scheduling problem with multiple objective functions and travel time constraint is to determine the allocation of buses to customer service requests minimizing the number of buses and travel costs under the travel time restriction for each bus. For the scheduling, we first represent the scheduling problem using a graph and develop a hierarchical approach. Second, we develop a mathematical model based algorithm for the scheduling problem including heuristic methods. We tested the performance of the algorithm on instances with real data. As a result, the total number of buses and travel costs are reduced over about 10% comparing with that of current practice at the company.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.154-161
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• 2010

This paper considers the simultaneously firing model for the artillery operations. The objective of this paper is to find the optimal fire sequence minimizing the final completion time of the firing missions of multiple artillery units for multiple targets. In the problem analysis, we derive several solution properties to reduce the solution space. Moreover, two lower bounds of objective are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed branch-and-bound and heuristic algorithms are evaluated through various numerical experiments.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.1-10
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• 2006

Many of statistical experimental designs have multiple goals. It is often impractical to use the single-objective criterion for this purpose. It is necessary to modify the existing optimum experimental design criteria. There exist three criteria handling this problem in general: compound, constrained, maxi-min approach. This paper extends Kahng and Kim's idea to develop another approach to incorporate several experimental design criteria in accordance of their importance in practical way. Furthermore this paper investigate its relationship with the maxi-min approach. It shows logically that the often realized infeasibility can be still avoided with the rank of importance of the objectives intact.

• Journal of KSNVE
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• v.9 no.5
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• pp.922-927
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• 1999

The objective of this paper is to obtain the contribution of each source to the spectrum of pressure, when there are multiple incoherent sources in near-field acoustic holography. For this objective, we have to obtain signals very coherent to the input signals of the sources. To obtain the very coherent signals, many people have measured pressure signals in the vincinity of the sources. However, it is sometimes difficult to locate microphones near to the sources so that the signals are very coherent to the input signals. This paper proposed a method to obtain the very coherent signals by near-field acoustic holography. Therefore, the proposed method does not require the measurement of pressure near to each source. Simulation results for two incoherent monopole sources showed the possibility of the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.220-226
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• 2000

The problem (P) of optimizing a linear function $d^Tx$ over the set of efficient points for a multiple objective linear program (M) is difficult because the efficient set is nonconvex. There are some interesting properties between the objective linear vector d and the matrix of multiple objectives C and those properties lead us to establish criteria to solve (P) with a linear program. In this paper we investigate a system of the linear equations $C^T{\alpha}$ = d and construct two linearly independent positive vectors u, v such that ${\alpha}$ = u - v. From those vectors u, v, solving an weighted sum linear program for finding an efficient extreme point for the (M) is a way of getting an optimal solution of the problem (P). Therefore the theorems presented in this paper provided us an easy way of solving nonconvex program (P) with a weighted sum linear program.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.4
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• pp.185-194
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• 2000

The learning automaton is an automaton to update systematically the strategy for enhancing the performance in response to the output results, and several schemes of learning automata have been presented. In this paper, S-model learning automata are applied in order to achieve the best compromise solution between an optimal solution for economic operation and an optimal solution for stable operation of the power system under the circumstance that the loads vary randomly. It is shown that learning automata are applied satisfactorily to the multiobjective optimization problem for obtaining the best tradeoff among the conflicting economy and stability objectives of power systems.

• International Journal of High-Rise Buildings
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• v.7 no.2
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• pp.161-170
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• 2018

Rapid urbanization, resource depletion, and limited land are further increasing the need for skyscrapers in city centers; therefore, it is imperative to enhance tall building performance efficiency and energy-generative capability. Potential performance improvements can be explored using parametric multi-objective optimization, aided by evaluation tools, such as computational fluid dynamics and energy analysis software, to visualize and explore skyscrapers' multi-resource, multi-system generative potential. An optimization-centered, software-based design platform can potentially enable the simultaneous exploration of multiple strategies for the decreased consumption and large-scale production of multiple resources. Resource Generative Skyscrapers (RGS) are proposed as a possible solution to further explore and optimize the generative potentials of skyscrapers. RGS can be optimized with waste-energy-harvesting capabilities by capitalizing on passive features of integrated renewable systems. This paper describes various resource-generation technologies suitable for a synergetic integration within the RGS typology, and the software tools that can facilitate exploration of their optimal use.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.299-319
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• 1997

Since a convergence strategy in interactive procedure is the origin of a lot of the restrictions and inconvenience of many methods, a new flexible convergence strategy is necessary for developing that is applicable for interactive MOLP as well as interactive multiple objective integer programming(MOIP). A method for computing the volume of the interval defined subsets of weighting vector space is developed using Sobol's LP$_{i}$, Generator. Since the interactive procedure requires a number of iterations, with a fixed number of solutions presented per iteration, a convergence strategy is needed to control the rate at which the interactive procedure converges to a final solution. Thus, in this paper, a new convergency strategy is developed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.375-383
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• 2000

This research suggests an interactive methodology fur multiple objective linear programming problems to help the group select a compromising solution in the World Wide Web environment. Our methodology lessens the burden of group decision makers, which is one of necessary conditions of the web environment. Only the partial weak order of variables and objectives from the group decision makers are enough for searching the best compromising solution. For such a purpose, we expand the Dror and Gass algorithm to the group decision context. And we suggest the system architecture of a web-based GDSS fur the implementation of our methodology.