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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

Fuzzy inventory models

TL;DR: An overview of the fuzzy inventory models literature gathering 210 papers from 1987 onward is given and several aspects of the models are assessed that led to identification of some areas overlooked by researchers so far.
Journal Article

A review and classification of fuzzy mathematical programs

TL;DR: Fifteen types of the fuzzy mathematical programming models are identified in the proposed classification and all possible combinations of fuzzy components are considered in classifying fuzzy mathematical programs.
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Fuzzy mixed-integer linear programming model for optimizing a multi-functional bioenergy system with biochar production for negative carbon emissions

TL;DR: In this paper, a fuzzy mixed-integer linear programming model is developed to simultaneously design and optimize a multi-functional bioenergy system given multiple product demands, carbon footprint, and economic performance constraints.
Journal ArticleDOI

Interactive fuzzy linear programming

TL;DR: This paper provides a practical modelling method which is a symmetric integration of Zimmermann's, Werners's, Vergegay's and Chanas's fuzzy LP approaches and additionally provides a decision support system for solving a specific domain of practical LP problems.
Journal ArticleDOI

Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment

TL;DR: This study delineates the stated formulation in which the total transportation cost, transportation time, and carbon emission cost from existing sites to p-facilities will be minimized and a hybrid approach is improved based on an alternating locate-allocate heuristic and the neutrosophic compromise programming to obtain the non-dominated solution.
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.
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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.