An interactive fuzzy satisficing method using augmented minimax problems and its application to environmental systems

Sakawa, Masatoshi; Yano, Hitoshi

doi:10.1109/tsmc.1985.6313455

Cited by 85 publications

(30 citation statements)

References 16 publications

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“…In this section, we introduce the interactive fuzzy satisficing method proposed by Sakawa and Yano [16] in order to find a satisficing solution of (9) for the DM.…”

Section: Interactive Fuzzy Satisficing Approachmentioning

confidence: 99%

“…The interactive fuzzy satisficing method [16] is to find a satisficing M-Pareto optimal solution through interaction to the DM. Let ) , ( 2 1 μ μ be a pair of initial reference membership levels of membership function 1 μ and 2 μ , respectively.…”

Section: Definition 1: Solution *mentioning

confidence: 99%

“…For finding a satisficing solution of the multiobjective EFLP for the decision maker (DM), we apply interactive fuzzy satisficing method proposed by Sakawa and Yano [16]. Katagiri et al [17] recently proposed interactive fuzzy satisficing method for multiobjective fuzzy random linear programming problems.…”

Section: Introductionmentioning

confidence: 99%

“…For the formulated EFLP, first we propose the method to compute the objective values for each location in Section 4. In order to find a satisficing solution for the DM, we introduce the interactive fuzzy satisficing method proposed by Sakawa and Yano [16] in Section 5. In order to solve the minimax problems in this method, we proposed a PSO method considering characteristics of the EFLP in Section 6.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Fuzzy Model for the Multiobjective Emergency Facility Location Problem with A-Distance

Uno

Katagiri²,

Kato³

2007

TOCSJ

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This paper proposes a new multiobjective location problem for emergency facilities, e.g. ambulance service stations and fire stations. In the problem, one of the objectives is to minimize the maximal distance of the paths from the located emergency facilities to hospitals via accidents. The other is to maximize the frequency of accidents that the emergency facilities can respond quickly. An interactive fuzzy satisficing method with particle swarm optimization (PSO) method is proposed for finding a satisficing location for the problem. Computational results illustrate the method with numerical examples of the multiobjective location problem.

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“…In this section, we introduce the interactive fuzzy satisficing method proposed by Sakawa and Yano [16] in order to find a satisficing solution of (9) for the DM.…”

Section: Interactive Fuzzy Satisficing Approachmentioning

confidence: 99%

Section: Definition 1: Solution *mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Fuzzy Model for the Multiobjective Emergency Facility Location Problem with A-Distance

Uno

Katagiri²,

Kato³

2007

TOCSJ

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“…Unfortunately, however, in their method, since membership functions for the objective functions are supposed to be aggregated by a minimum operator or a product operator, optimal solutions which sufficiently reflect the DM's preference may not be obtained. To cope with the problem, after reformulating multiobjective stochastic linear programming problems using several models for chance constrained programming, Sakawa et al [24,23,25] presented an interactive fuzzy satisficing method to derive a satisficing solution for the DM as a generalization of their previous results [33,36,34,35,21].…”

Section: Introductionmentioning

confidence: 99%

Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization

Sakawa

Matsui²

2013

AIR

Self Cite

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ForewordIn this paper, we focus on stochastic two-level linear programming problems involving random variable coefficients both in objective functions and constraints. Using the concept of chance constraints, stochastic constraints are transformed into deterministic ones. Following the probability maximization model, the minimization of each stochastic objective function is replaced with the maximization of the probability that each objective function is less than or equal to a certain value. Under some appropriate assumptions for distribution functions, the formulated stochastic two-level linear programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at both levels, a satisfactory solution is derived efficiently by updating the satisfactory degree of the decision maker at the upper level with considerations of overall satisfactory balance among both levels. It should be emphasized here that the transformed deterministic problems for deriving an overall satisfactory solution can be easily solved through the combined use of the bisection method and the phase one of the simplex method. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.-iii - AbstractThis paper considers stochastic two-level linear programming problems. Using the concept of chance constraints and probability maximization, original problems are transformed into deterministic ones. An interactive fuzzy programming method is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance.

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An interactive fuzzy satisficing method for multiobjective nonconvex programming problems through floating-point genetic algorithms

Sakawa

Yauchi

2000

Electron. Comm. Jpn. Pt. III

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An interactive fuzzy satisficing method using augmented minimax problems and its application to environmental systems

Cited by 85 publications

References 16 publications

A Fuzzy Model for the Multiobjective Emergency Facility Location Problem with A-Distance

A Fuzzy Model for the Multiobjective Emergency Facility Location Problem with A-Distance

Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization

An interactive fuzzy satisficing method for multiobjective nonconvex programming problems through floating-point genetic algorithms

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