5 research outputs found

    Rule sets based bilevel decision model

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    Bilevel decision addresses the problem in which two levels of decision makers, each tries to optimize their individual objectives under constraints, act and react in an uncooperative, sequential manner. Such a bilevel optimization structure appears naturally in many aspects of planning, management and policy making. However, bilevel decision making may involve many uncertain factors in a real world problem. Therefore it is hard to determine the objective functions and constraints of the leader and the follower when build a bilevel decision model. To deal with this issue, this study explores the use of rule sets to format a bilevel decision problem by establishing a rule sets based model. After develop a method to construct a rule sets based bilevel model of a real-world problem, an example to illustrate the construction process is presented. Copyright © 2006, Australian Computer Society, Inc

    An algorithm for solving rule sets-based bilevel decision problems

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    Bilevel decision addresses the problem in which two levels of decision makers each tries to optimize their individual objectives under certain constraints, and to act and react in an uncooperative and sequential manner. Given the difficulty of formulating a bilevel decision problem by mathematical functions, a rule sets-based bilevel decision (RSBLD) model was proposed. This article presents an algorithm to solve a RSBLD problem. A case-based example is given to illustrate the functions of the proposed algorithm. Finally, a set of experiments is analyzed to further show the functions and the effectiveness of the proposed algorithm. © 2011 Wiley Periodicals, Inc

    Fault diagnosis of transformer using association rule mining and knowledge base

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    Association rule mining makes interesting associations and/or correlations among large sets of data. Those associations can be refined as decision rules to be used and stored in a knowledge base system. In this paper, an approach based on association rule and knowledge base is proposed and implemented in the fault diagnosis of a transformer system. According to the features of association rule, the Apriori algorithm is adopted and modified to generate decision rules from power transformer information for building knowledge base, then the rules can be refined to diagnose the fault of the transformer through reasoning, and a prototype system is developed. This approach based on association rule is described in detail and the application is illustrated by an example. A comparison with the IEC (International Electrotechnical Commission) three-ratio method shows the proposed method can provide better accuracy in performance. © 2010 IEEE

    A new solution algorithm for solving rule-sets based bilevel decision problems

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    Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd. Bilevel decision addresses compromises between two interacting decision entities within a given hierarchical complex system under distributed environments. Bilevel programming typically solves bilevel decision problems. However, formulation of objectives and constraints in mathematical functions is required, which are difficult, and sometimes impossible, in real-world situations because of various uncertainties. Our study develops a rule-set based bilevel decision approach, which models a bilevel decision problem by creating, transforming and reducing related rule sets. This study develops a new rule-sets based solution algorithm to obtain an optimal solution from the bilevel decision problem described by rule sets. A case study and a set of experiments illustrate both functions and the effectiveness of the developed algorithm in solving a bilevel decision problem

    Rule sets based bilevel decision model and algorithm

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    Bilevel decision addresses the problem in which two levels of decision makers, each tries to optimize their individual objectives under certain constraints, act and react in an uncooperative, sequential manner. As bilevel decision making often involves many uncertain factors in real world problems, it is hard to formulate the objective functions and constraints of the leader and the follower in modelling a real bilevel decision problem. This study explores a new approach that uses rule sets to formulate a bilevel decision problem. It first develops related theories to prove the feasibility to model a bilevel decision problem by rule sets. It then proposes an algorithm to describe the modelling process. A case study is discussed to illustrate the functions and effectiveness of the proposed rule sets based bilevel decision modelling algorithm. © 2007 Elsevier Ltd. All rights reserved
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