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https://hdl.handle.net/2142/67027
Description
Title
Strategies in Multiple Criteria Decision Making
Author(s)
Ghiassi, Manoochehr
Issue Date
1980
Department of Study
Mechanical Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Mechanical
Language
eng
Abstract
The Multiple Criteria Decision Making (MCDM) problem has been considered in its general form. The focus of this thesis, however, is on multiple objective linear programming (MOLP) problems. The MCDM problem will first be examined for possible modifications in an attempt to resolve conflicts among the objectives. The concept of the range of compromise is introduced in this research. Determination of the range of compromise requires evaluation of two parameters n(,v), the minimum value that objective v can take within the nondominated set and M(,v), the maximum feasible value for objective v. An algorithm is developed to find n(,v). Evaluation of M(,v) is a straightforward linear programming problem.
A weighting method called "Dimensionless Weighting Method" is employed to solve the MOLP problem. Parameters M(,v), n(,v) and A(,v), an acceptable level for objective v, are used to define a number of weighting schemes to be used in aggregating objectives. To avoid the problem of dealing with several objective functions with differing dimensions, all the objective functions are transferred to dimensionless quantities. Two different kinds of composite functions are introduced: (i) the linearly weighted composite function, and (ii) the Minimax formulation. An interactive approach has been developed which will involve the decision maker in the decision making process.
Finally, the method of dimensionless weighting was applied to a metal cutting problem involving four objective functions. The range of compromise for each objective was calculated. A set of nondominated solutions were generated based on different rankings of the objectives.
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