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Journal ArticleDOI

Fuzzy programming and linear programming with several objective functions

Hans-Jürgen Zimmermann
- 01 Jan 1978 - 
- Vol. 1, Iss: 1, pp 45-55
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TLDR
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.
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This article is published in Fuzzy Sets and Systems.The article was published on 1978-01-01. It has received 3357 citations till now. The article focuses on the topics: Linear-fractional programming & Inductive programming.

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Citations
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Journal ArticleDOI

An integrated approach for deriving priorities in analytic network process

TL;DR: A multiple objective programming approach for the analytic network process (ANP) is proposed to obtain all local priorities for crisp or interval judgments at one time, even in an inconsistent situation, and can be regarded as an efficient alternative of the fuzzy ANP.
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A new hybrid algorithm of simulated annealing and simplex downhill for solving multiple-objective aggregate production planning on fuzzy environment

TL;DR: Experimental results indicate that the fuzzy–SASD is the most effectual of all approaches and consequently resolve APP problems in a fuzzy environment.
Journal ArticleDOI

A fuzzy grey goal programming approach for aggregate production planning

TL;DR: In this article, a multi-objective model is proposed for aggregate planning problem in which the parameters of the model are expressed in the form of grey numbers, and the model is applied in a real-world problem, and its results are illustrated.
Journal ArticleDOI

Fuzzy multi-choice goal programming

TL;DR: A novel formulation of fuzzy multi-choice goal programming (FMCGP) is presented that not only improves the applicability of goal programming in real world situations but also provides useful insight about the solution of a new class of problems.
Journal ArticleDOI

Solving fuzzy multi-objective linear programming problems using deviation degree measures and weighted max–min method

TL;DR: An algorithm to find a balance-pareto-optimal solution between two goals in conflict: to improve the objectives function values and to decrease the values of the deviation degrees.
References
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Book

Decision-making in a fuzzy environment

TL;DR: A reverse-flow technique is described for the solution of a functional equation arising in connection with a decision process in which the termination time is defined implicitly by the condition that the process stops when the system under control enters a specified set of states in its state space.
Book

Management Models and Industrial Applications of Linear Programming

TL;DR: In place of a survey or evaluation of industrial studies, two broad issues which are relevant to all such applications will be discussed, including the use of linear programming models as guides to data collection and analysis and prognosis of fruitful areas of additional research, especially those which appear to have been opened by industrial applications.
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Linear programming with multiple objective functions: Step method (stem)

TL;DR: In this man-model symbiosis, phases of computation alternate with phases of decision, which allows the decision-maker to “learn” to recognize good solutions and the relative importance of the objectives.
Journal ArticleDOI

Description and optimization of fuzzy systems

TL;DR: Fuzzy set theory is applied to fuzzy linear programming problems and it is shown how fuzzylinear programming problems can be solved without increasing the computational effort.
Journal ArticleDOI

Interactive approach for multi-criterion optimization, with an application to the operation of an academic department.

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.