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Multiple Criteria Optimization: Theory, Computation, and Application
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Mathematical Background Topics from Linear Algebra Single Objective Linear Programming Determining all Alternative Optima Comments about Objective Row Parametric Programming Utility Functions, Nondominated Criterion Vectors and Efficient Points Point Estimate Weighted-sums Approach.Abstract:
Mathematical Background Topics from Linear Algebra Single Objective Linear Programming Determining all Alternative Optima Comments about Objective Row Parametric Programming Utility Functions, Nondominated Criterion Vectors and Efficient Points Point Estimate Weighted-sums Approach Optimal Weighting Vectors, Scaling and Reduced Feasible Region Methods Vector-Maximum Algorithms Goal Programming Filtering and Set Discretization Multiple Objective Linear Fractional Programming Interactive Procedures Interactive Weighted Tchebycheff Procedure Tchebycheff/Weighted-Sums Implementation Applications Future Directions Index.read more
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The process of multiattribute decision making: A case study of selecting applicants for a Ph.D. program
TL;DR: The process of how individuals make decisions in a deterministic, multiattribute decision environment is investigated in a large US university, where three faculty members made decisions and recommendations about accepting or rejecting applications for their department's Ph.D. program.
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A fuzzy bi-objective mixed-integer programming method for solving supply chain network design problems under ambiguous and vague conditions
TL;DR: This work uses a computationally efficient ranking method to resolve the ambiguity of the parameters and proposes two methods for resolving the vagueness of the objective functions in the proposed fuzzy MILP model to enhance the material flow in dual-channel, multi-item, and multi-objective SCs with multiple echelons under both ambiguous and vague conditions.
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Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations
Tim Holzmann,J.C. Smith +1 more
TL;DR: This is the first generating method for general discrete multi-objective problems that uses a variant of the Tchebychev norm, and in a computational study, the algorithm’s running times are comparable to previously proposed algorithms.
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Pareto optimal design of absorbers using a parallel elitist nondominated sorting genetic algorithm and the finite element-boundary integral method
TL;DR: Numerical tests demonstrate that the elitist NSGA proposed in this paper converges faster that the standard NSGA and other classical techniques for a wide variety of absorber design problems.
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Box-triangular multiobjective linear programs for resource allocation with application to load management and energy market problems
Petr Ekel,E. A. Galperin +1 more
TL;DR: In this article, a model for multicriteria resource allocation with the specific box-triangular structure of a feasible region is constructed with the method of balance set equations for the satisfaction level representation of the cost function space including the case of linearly dependent cost functions.