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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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Applications of the Non-Dominated Sorting Genetic Algorithm (NSGA) in Chemical Reaction Engineering

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Multi-stage stochastic mean-semivariance-CVaR portfolio optimization under transaction costs

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Saddle Points and Pareto Points in Multiple Objective Programming

TL;DR: In this paper relationships between Pareto points and saddle points are studied in convex and nonconvex multiple objective programming.