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Journal ArticleDOI

Bi-criteria multi facility location problem in fuzzy environment

10 Jun 1993-Fuzzy Sets and Systems (North-Holland)-Vol. 56, Iss: 2, pp 145-153
TL;DR: In this article, a fuzzy goal programming model for locating multiple new facilities on a plane bounded by a convex polygon under the criteria: (1) minimize the sum of all the transportation costs and (2) minimise the maximum distances from the facilities to the demand points.
About: This article is published in Fuzzy Sets and Systems.The article was published on 1993-06-10. It has received 43 citations till now. The article focuses on the topics: Convex polygon & Facility location problem.
Citations
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Journal ArticleDOI
TL;DR: This paper considers location–allocation problem in the real uncertain world and develops a possibilistic non-linear programming model to deal with this problem and uses a hybrid chromosome structure to solve this model.
Abstract: This paper considers location–allocation problem in the real uncertain world and develops a possibilistic non-linear programming model to deal with this problem. Fuzzy decision making in fuzzy environment concept is used to determine possibility distribution of location and allocation variables. To solve this model, a novel approach based on genetic algorithm structure is developed. As the proposed model includes both deterministic (location) and uncertain (allocation) parameters, the developed solution algorithm uses a hybrid chromosome structure. Also, to cover continuous nature of the problem and prevent GA from early convergence, a new crossover operator is introduced. Finally, performance of the developed algorithm is evaluated by an example.

14 citations


Cites background from "Bi-criteria multi facility location..."

  • ...Also various facility location problems in fuzzy environment are discussed by Darzentas [16], Bhattacharya et al. [ 17 ], and ChenandWei[18]....

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Journal ArticleDOI
TL;DR: Three fuzzy random programming models based on the mean chance for the capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected cost minimization model, the α-cost minimization models, and the chance maximization model.

13 citations


Cites methods from "Bi-criteria multi facility location..."

  • ...Besides, many other fuzzy programming models as well as corresponding algorithms have also been presented for the location-allocation problem in Bhattacharya, Rao, and Tiwari (1993), Chen and Wei (1998), Liu and Zhu (2007)....

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Journal ArticleDOI
28 May 2019
TL;DR: A multi-objective, bilevel optimization model to relocate surviving sensors to maximize an intruder’s minimal expected exposure to traverse a defended border region, minimize the maximum sensor relocation time, and minimize the total number of sensors requiring relocation is formulated.
Abstract: Consider a set of sensors having varying capabilities and respectively located to maximize an intruder’s minimal expected exposure to traverse a defended border region. Given two subsets of...

11 citations

Proceedings ArticleDOI
19 Jun 1996
TL;DR: A method to solve qualitative locational choice problems using fuzzy decision tables as a matching model and PROLOGA, an interactive rule-based design tool for decision table construction, optimization and manipulation is proposed.
Abstract: Proposes a method to solve qualitative locational choice problems using fuzzy decision tables as a matching model. Firstly, the technique of crisp decision tables is explained, and their use in locational choice problems is advocated. Subsequently, fuzzy extensions of decision tables are defined. Next, using a brief example, it is shown that fuzzy decision tables can be used efficiently for evaluating business location problems. The proposed method is supported by PROLOGA, an interactive rule-based design tool for decision table construction, optimization and manipulation.

9 citations

Proceedings ArticleDOI
08 Sep 1996
TL;DR: It is explained how the techniques of fuzzy decision tables can used for business site selection and how this technique fits in the spectrum of techniques which can be adopted forbusiness site selection.
Abstract: It is explained how the techniques of fuzzy decision tables can used for business site selection. It is outlined how this technique fits in the spectrum of techniques which can be adopted for business site selection. Furthermore, it is described how decision tables can be modelled based on functional equivalence. The decision tables are modelled with a tool called Prologa. This tool supports the interactive construction, optimization and consultation of knowledge structuring formalisms such as decision tables, decision rules and decision trees.

9 citations

References
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Journal ArticleDOI
E. T. Jaynes1
TL;DR: In this article, the authors consider statistical mechanics as a form of statistical inference rather than as a physical theory, and show that the usual computational rules, starting with the determination of the partition function, are an immediate consequence of the maximum-entropy principle.
Abstract: Information theory provides a constructive criterion for setting up probability distributions on the basis of partial knowledge, and leads to a type of statistical inference which is called the maximum-entropy estimate. It is the least biased estimate possible on the given information; i.e., it is maximally noncommittal with regard to missing information. If one considers statistical mechanics as a form of statistical inference rather than as a physical theory, it is found that the usual computational rules, starting with the determination of the partition function, are an immediate consequence of the maximum-entropy principle. In the resulting "subjective statistical mechanics," the usual rules are thus justified independently of any physical argument, and in particular independently of experimental verification; whether or not the results agree with experiment, they still represent the best estimates that could have been made on the basis of the information available.It is concluded that statistical mechanics need not be regarded as a physical theory dependent for its validity on the truth of additional assumptions not contained in the laws of mechanics (such as ergodicity, metric transitivity, equal a priori probabilities, etc.). Furthermore, it is possible to maintain a sharp distinction between its physical and statistical aspects. The former consists only of the correct enumeration of the states of a system and their properties; the latter is a straightforward example of statistical inference.

12,099 citations

Journal ArticleDOI
TL;DR: It is shown that solutions obtained by fuzzy linear programming are always efficient solutions and the consequences of using different ways of combining individual objective functions in order to determine an “optimal” compromise solution are shown.

3,357 citations

Journal ArticleDOI
TL;DR: In this paper, the concept of proper efficiency was introduced to eliminate efficient points of a certain anomalous nature in the problem of vector maximization, which is related in spirit to the notion of "proper" efficiency introduced by Kuhn and Tucker in their celebrated paper of 1950.

1,272 citations

Journal ArticleDOI
TL;DR: An interactive mathematical programming approach to multi-criterion optimization is developed, and then illustrated by an application to the aggregated operating problem of an academic department.
Abstract: An interactive mathematical programming approach to multi-criterion optimization is developed, and then illustrated by an application to the aggregated operating problem of an academic department.

837 citations

Journal ArticleDOI
01 Jan 1973
TL;DR: The main concern is with the application of the theory of fuzzy sets to decision problems involving fuzzy goals and strategies, etc., as defined by R. E. Bellman and L. A. Zadeh.
Abstract: In problems of system analysis, it is customary to treat imprecision by the use of probability theory. It is becoming increasingly clear, however, that in the case of many real world problems involving large scale systems such as economic systems, social systems, mass service systems, etc., the major source of imprecision should more properly be labeled ‘fuzziness’ rather than ‘randomness.’ By fuzziness, we mean the type of imprecision which is associated with the lack of sharp transition from membership to nonmembership, as in tall men, small numbers, likely events, etc. In this paper our main concern is with the application of the theory of fuzzy sets to decision problems involving fuzzy goals and strategies, etc., as defined by R. E. Bellman and L. A. Zadeh [1]. However, in our approach, the emphasis is on mathematical programming and the use of the concept of a level set to extend some of the classical results to problems involving fuzzy constraints and objective functions.

593 citations