• 제목/요약/키워드: conflicting objectives

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Fuzzy 다목적 선형계획법을 이용한 최적 무효전력 배분계획에 관한 연구 (A study on the Optimal VAR allocation Using Fuzzy Linear Programming with Multi-criteria function)

  • 송길영;이희영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1992년도 하계학술대회 논문집 A
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    • pp.211-213
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    • 1992
  • Fuzzy L. P. with Multi-criteria function is adopted in this VAR allocation algorithm to accomplish the optimization of co-conflicting objectives, such as the amount of the VAR Installed and power system loss, while keeping the bus voltage profile within an admissible range. fuzzy L. P., a powerful tool dealing with the fuzziness of satisfaction levels of the constraints and the goal of objective functions, enables us to search for the solutions which may contribute in VAR planning. This advantage Is not provided by traditional standardized L. P. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

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Clustering Parts Based on the Design and Manufacturing Similarities Using a Genetic Algorithm

  • Lee, Sung-Youl
    • 한국산업정보학회논문지
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    • 제16권4호
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    • pp.119-125
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    • 2011
  • The part family (PF) formation in a cellular manufacturing has been a key issue for the successful implementation of Group Technology (GT). Basically, a part has two different attributes; i.e., design and manufacturing. The respective similarity in both attributes is often conflicting each other. However, the two attributes should be taken into account appropriately in order for the PF to maximize the benefits of the GT implementation. This paper proposes a clustering algorithm which considers the two attributes simultaneously based on pareto optimal theory. The similarity in each attribute can be represented as two individual objective functions. Then, the resulting two objective functions are properly combined into a pareto fitness function which assigns a single fitness value to each solution based on the two objective functions. A GA is used to find the pareto optimal set of solutions based on the fitness function. A set of hypothetical parts are grouped using the proposed system. The results show that the proposed system is very promising in clustering with multiple objectives.

The Limitations of Risk-based Auditing using Fuzzy Methods

  • Mohammadi, Shaban
    • 산경연구논집
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    • 제6권1호
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    • pp.37-40
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    • 2015
  • Purpose - Investors, creditors, governments, and others make decisions using reasonable information provided by others. In many cases, the users of this information have goals and objectives conflicting with those of the information's producers, indicating the need for external auditors. Research design, data, and methodology - Competition in auditing has noticeably intensified globally, especially in developed countries. This means that auditors are striving to increase the efficiency of their methods. In recent years, risk-based auditing has become prominent among these efforts. In risk-assessment auditing, the auditor may directly affect the effectiveness and efficiency of the audit. Results - As a central framework, the risk assessment process improves audit quality and effectiveness such that the audit will lead to necessary changes. Previous studies have shown that risk assessment affects the nature, timing, and content of audit procedures. Conclusions - In the planning stage of an audit, audit risk assessment may identify any inappropriate or inefficient distribution of resources or determine whether the results of an audit will be ineffective or incorrect. Thus, assessing audit risk is a critical task.

다목적을 고려한 전력 시스템의 최적운용을 위한 S 모델 Automata의 적용 연구 (A Study on the Application of S Model Automata for Multiple Objective Optimal Operation of Power Systems)

  • 이병하;박종근
    • 대한전기학회논문지:전력기술부문A
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    • 제49권4호
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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.

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MCDM 모델을 이용한 재활용 제조부품 관리 (Management of Recycling-Oriented Manufacturing Components Based on an MCDM Model)

  • 신완선;오현주
    • 대한산업공학회지
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    • 제22권4호
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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.

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An optimization usability of information system project resources: using a QFD and Zero-One Goal Programming for reflection customer wants

  • Kim, Soung-Hie;Lee, Jin-Woo
    • 한국국방경영분석학회지
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    • 제26권1호
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    • pp.100-114
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    • 2000
  • This paper demonstrates the application of a Quality Function Deployment (QFD) and Zero-One Goal Programming model for selecting interdependent information system project selection, there are a few research for interdependent IS project selection. Effective project evaluation necessities incorporating the many conflicting objectives of decision maker(s) into decision models. Among the many proposed methodologies of multi-criteria decision making (MCDM), Goal Programming (GP) is the most popular and widely used. The model departs from an earlier GP formulation of the problem that suggested QFD method for selection of priorities among the considered attributes or criteria. The application of the proposed methodology illustrated through an example.

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How to Build a Learning Capability for Innovation? A Framework of Market-Based Learning Process

  • Lee, Hyun Jung;Park, Jeong Eun;Pae, Jae Hyun
    • Asia Marketing Journal
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    • 제17권1호
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    • pp.27-53
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    • 2015
  • Learning organization has been an important issue in both management and marketing areas. Also learning capability is a key construct of innovation process in a firm. Especially, in marketing context, several researchers have studied market-based learning and its relation with performance. Previous studies have shown that market-based learning has a positive impact on overall firm performance. However, there has been inconsistency in the concept of market-based learning itself and its relationships with antecedents and consequences. Given this conflicting and inconsistent results of previous research, this study has two main objectives. First, this paper proposed a conceptual framework that marketbased learning has two types of processes and each types of market-based learning will generate different types of performance. Second, the mediating role of marketing capability in learning-performance link is proposed. The proposed conceptual framework shows that organizations which have marketbased learning for innovation management can enjoy ambidextrous firm performance on both side of effectiveness and efficiency via marketing capability. Moreover our research model proposes key drivers of market based organizational learning.

사교육서비스 분야에서의 BSC 모델 개발 및 전략실행방안에 관한 연구 (A Study on BSC development and Strategy execution plan for Private education service field)

  • 정민의;유성진
    • 품질경영학회지
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    • 제42권3호
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    • pp.425-444
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    • 2014
  • Purpose: This study aims to overcome the problem of private education market environment which is polarized into commercialized large private education institutions and small and medium sized private education institutions in a poor business environment, and develop systematic performance measurement model applicable for small and medium sized private education institutions. Methods: To develop the BSC which measures financial and non-financial indicator in a balanced manner and introduce the BSC into private education institutions that contain conflicting goals "EDUCATION" and "PROFIT". In particular, Utilizing the methodology of AHP, the priority of strategies and execution assignments are derived. Results: BSC model was developed and introduced by cooperating with executives of the private education institution. Moreover, the study permits to achieve the strategy, enterprise-wide vision and mission by deriving strategy map and applying it to the private education institution. To measure the performance of BSC model instruction, KPI corresponding to the strategic objectives of each perspective was derived. Conclusion: BSC model generally introduces to large-sized companies and public institutions. In this study, BSC model is developed by focusing on small and medium sized private institution. Furthermore, this study is more than simple model development, it makes a connection with achievement of strategic objectives, enterprise-wide vision and mission through strategy map and strategy execution method. Through the developed BSC model and strategy execution method, utilization plan in practice and customized model for private education institutions coexisting profit and non-profit objectives were developed, and academic implications were presented.

A Bi-objective Game-based Task Scheduling Method in Cloud Computing Environment

  • Guo, Wanwan;Zhao, Mengkai;Cui, Zhihua;Xie, Liping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3565-3583
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    • 2022
  • The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

유전 알고리즘을 이용한 이중목적 최단경로 모형개발에 관한 연구 (A Study On Bi-Criteria Shortest Path Model Development Using Genetic Algorithm)

  • 이승재;장인성;박민희
    • 대한교통학회지
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    • 제18권3호
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    • pp.77-86
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    • 2000
  • 기존의 최단경로 탐색모형은 단일 목적을 대상으로 한다. 그러나 실제로는 통행자가 단일 목적만을 기준으로 경로를 선택하는 경우는 드물며, 경로선택은 통행시간과 비용 등 다양한 목적을 종합적으로 고려해서 결정되어진다. 따라서 최단경로는 여러 가지 목적을 고려해야 한다. 이러한 경우에 이들 목적간의 상충적인 관계로 인해 여러 가지 목적을 모두 만족시키는 최적경로는 존재치 않으며, 통행자가 고려하는 목적들의 중요도에 따라 다양한 경로가 선택되어질 수 있다. 다목적의 최적경로는 여러 가지 목적들의 절충(Trade-Off)을 고려한 다수의 파레토 최적경로(Pareto Optimal Path)가 탐색되어져야 한다. 그러나 기존의 다중목적을 고려한 최적경로 탐색 알고리즘은 하나 또는 일부의 파레토 최적경로만을 탐색하며 따라서 다양한 경로를 제공하지 못한다. 본 논문은 두 개의 목적을 고려한 최적경로 탐색 모형을 개발하는 것이다. 파레토 최적경로들은 대체경로로 사용할 수도 있다. 본 연구에서는 다양한 파레토 최적경로를 탐색하기 위해 본 모형의 개발에 유전 알고리즘(Genetic Algorithm)을 적용하였다.

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