• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.33-40
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• 1997

An optimization system, APROGA II using genetic algorithm, was developed to solve multi-modal and multiobjective problems. To begin with, Multi-Niche Crowding(MNC) algorithm was used for multi-modal optimization problem. Secondly, a new algorithm was suggested for multiobjective optimization problem. Pareto dominance tournaments and Sharing on the non-dominated frontier was applied to it to obtain multiple objectives. APROGA II uses these two algorithms and the system has three search engines(previous APROGA search engine, multi-modal search engine and multiobjective search engine). Besides, this system can handle binary and discrete variables. And the validity of APROGA II was proved by solving several test functions and case study problems successfully.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.374-384
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• 2016

The efficiency of a supply chain can be extremely affected by its design which includes determining the flow pattern of material from suppliers to costumers, selecting the suppliers, and defining the opened facilities in network. In this paper, a multi-objective multi-echelon multi-product supply chain design model is proposed in which several suppliers, several manufacturers, several distribution centers as different stages of supply chain cooperate with each other to satisfy various costumers' demands. The multi-objectives of this model which considered simultaneously are 1-minimize the total cost of supply chain including production cost, transportation cost, shortage cost, and costs of opening a facility, 2-minimize the transportation time from suppliers to costumers, and 3-maximize the service level of the system by minimizing the maximum level of shortages. To configure this model a graph theoretic approach is used by considering channels among each two facilities as links and each facility as the nodes in this configuration. Based on complexity of the proposed model a multi-objective Pareto-based vibration damping optimization (VDO) algorithm is applied to solve the model and finally non-dominated sorting genetic algorithm (NSGA-II) is also applied to evaluate the performance of MOVDO. The results indicated the effectiveness of the proposed MOVDO to solve the model.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2187-2195
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• 2018

In order to realize the multi-objective control of single-input multi-output nonlinear differential algebraic system (NDAS) and to improve the dynamic characteristics and static accuracy, a design method of nonlinear control with multi-objective feedback (NCMOF) is proposed, the principium of this method to arrange system poles, as well as its nature to coordinate dynamic characteristics and static accuracy of the system are analyzed in detail. Through NCMOF design method, the multi-objective control of the system is transformed into linear space, and then it is effectively controlled under the nonlinear feedback control law, the problem to balance all control objectives caused by less input and more output of the system thus is solved. Applying NCMOF design method to generator excitation system, the nonlinear excitation control law with terminal voltage, active power and rotor speed as objective outputs is designed. Simulation results show that NCMOF can not only improve the dynamic characteristics of generator, but also damp the mechanical oscillation of a generator in transient process. Moreover, NCMOF can control the terminal voltage of the generator to the setting value with no static error under typical disturbances.

• The Korean Journal of Community Living Science
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• v.27 no.1
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• pp.95-108
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• 2016

The objectives of this study are to analyze the characteristics of multi-cultural families in rural areas and to classify their types by applying multi-variate techniques and cluster analyses. Data for the study were obtained by a surveying 120 married migrant females in rural areas of Chungchengnam-do, South Korea. By utilizing the factor analysis to analyze the characteristics of multi-cultural families, 16 basic variables related to these female subjects were categorized into 6 factors: 'marriage length and age', 'language skill of migrant female', 'language skill of husband', 'family satisfaction', 'income and education', and 'general living satisfaction in Korea with remittance'. By appling the cluster analysis, multi-cultural families in rural areas were divided into the following 5 types: 'stable settlement', 'average but stagnant', 'below average yet positive', 'high- income with little communication', and 'young low-income'. In all types, it is strongly recommended to develop various programs regarding vocational education for the migrant females in order to increase their economic opportunities as well as social status.

• Steel and Composite Structures
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• v.33 no.6
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• pp.767-776
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• 2019

In this article, a simple and robust multi-objective assessment method to control design angles and node positions connected among steel outrigger truss members is proposed to approve both structural safety and economical cost. For given outrigger member layouts, the present method utilizes general-purpose prototypes of outrigger members, having resistance to withstand lateral load effects directly applied to tall buildings, which conform to variable connecting node and design space deposition. Outrigger layouts are set into several initial design conditions of height to width of an arbitrary given design space, i.e., variable design space. And then they are assessed in terms of a proposed multi-objective function optimizing both minimal total displacement and material quantity subjected to design impact factor indicating the importance of objectives. To evaluate the proposed multi-objective function, an analysis model uses a modified Maxwell-Mohr method, and an optimization model is defined by a ground structure assuming arbitrary discrete straight members. It provides a new robust assessment model from a local design point of view, as it may produce specific optimal prototypes of outrigger layouts corresponding to arbitrary height and width ratio of design space. Numerical examples verify the validity and robustness of the present assessment method for controlling prototypes of outrigger truss members considering a multi-objective optimization achieving structural safety and material cost.

• Journal of Korean Association for Spatial Structures
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• v.3 no.2 s.8
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• pp.77-83
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• 2003

This paper presents decision making method of structural multi-objective fuzzy optimum problem. The data and behavior of many engineering systems are not know precisely and the designer is required to design the system in the presence of fuzziness in the multi-goals, constraints and consequences of possible actions. In this paper, in order to find a satisfactory solution, the membership functions are constructed for the fuzzy objectives subject to the fuzzy constraints, and two approaches are presented by using the different types of fuzzy decision making. Thus, multi-objective fuzzy optimum problem can be converted into single objective non-fuzzy optimum problem and satisfactory solution of the multi-objective fuzzy optimum problem can be found with general optimum programming. Illustrative numerical example of the ten bar truss for minimum weight and minimum deflection is provided to demonstrate the process of finding the solution and the results are discussed.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1479-1486
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• 2016

According to the advancement of display devices, the multi-screen contents display environment is growing to be accepted for the display exhibition area. The objectives of this research are to find communications technology and to design an editor interface of contents delivery system for the larger and adaptive multi-display workspaces. The proposed system can find existence of display devices and get information without any additional tools like marker, and can recognize device layout with only web-cam and image processing technology. The multi-display contents delivery system is composed of devices with three roles; display device, editor device, and fixed server. The editor device which has the role of main control uses UPnP technology to find existence and receive information of display devices. extract appointed color in captured picture using a tracking library to recognize the physical layout of display devices. After the device information and physical layout of display devices are connected, the content delivery system allows the display contents to be sent to the corresponding display devices through WebSocket technology. Also the experimental results show the possibility of our device connection and layout recognition techniques can be utilized for the large spaced and adaptive multi-display applications.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.30-35
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• 2013

Motivated by the emergency scheduling in a transportation network, this paper considers a transportation problem, in which, the truck times and transportation costs are assumed as uncertain variables. To meet the demand in the practical applications, two optimization objectives are considered, one is the total costs and another is the completion times. And then, a multi-objective optimization model is developed according to the situation in applications. Because there are commensurability and conflicting between the two objectives commonly, a solution does not necessarily exist that is best with respective to the two objectives. Therefore, the problem is reduced to a single objective model, which is an uncertain programming with a chance-constrain. After some analysis, its equivalent deterministic form is obtained, which is a nonlinear programming. Based on a stepwise optimization strategy, a solution method is developed to solve the problem. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.367-380
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• 2019

The paper concerns topology and geometry optimization of statically determinate beams with arbitrary number of supports. The optimization problem is treated as a bi-criteria one, with the objectives of minimizing the absolute maximum bending moment and the maximum deflection for a uniform gravity load. The problem is formulated and solved using the Pareto optimality concept and the lexicographic ordering of the objectives. The non-dominated sorting genetic algorithm NSGA-II and the local search method are used for the optimization in the Pareto sense, whereas the genetic algorithm and the exhaustive search method for the lexicographic optimization. Trade-offs between objectives are examined and sets of Pareto-optimal solutions are provided for different topologies. Lexicographically optimal beams are found assuming that the maximum moment is a more important criterion. Exact formulas for locations and values of the maximum deflection are given for all lexicographically optimal beams of any topology and any number of supports. Topologies with lexicographically optimal geometries are classified into equivalence classes, and specific features of these classes are discussed. A qualitative principle of the division of topologies equivalent in terms of the maximum moment into topologies better and worse in terms of the maximum deflection is found.