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Multiple Criteria Optimization: Theory, Computation, and Application

R. S. Laundy
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TLDR
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.

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Journal ArticleDOI

Inferring Efficient Weights from Pairwise Comparison Matrices

TL;DR: A characterization of the set of efficient solutions is given, which enables us to assert that the least-logarithmic-squares solution is always efficient, whereas the (widely used) eigenvector solution is not, in some cases, efficient, thus its use in practice may be questionable.
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Measurement methods for product evaluation

TL;DR: In this paper, the authors apply mathematical measurement theory to analyze and clarify common design methods, and show that standard optimization methods operate with extensively measurable scales and concept selection charts operate with interval scales.
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Optimizing a linear function over an efficient set

TL;DR: In this paper, a technique for finding an optimal solution of (P) is presented, where two algorithms for solving the problem in a finite sequence of pivots are presented along with a numerical example.
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Measuring the efficiency of third party reverse logistics provider in supply chain by multi objective additive network DEA model

TL;DR: An optimisation model is introduced to define the technical and operative features of fleets, which maximises the success opportunities in terms of cost and time for multimodal chains against the road, and the most suitable fleets for the Sea Motorways Vigo-St.Nazaire and Gijon-Stazaire have been identified.
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Continuous Top-k Dominating Queries

TL;DR: This work contains the first study of continuous top-k dominating queries over data streams, and two approximate algorithms are proposed (AHBA and AMSA).