Nonscalarized multiobjective global optimization

TL;DR: The algorithm is an extension of the work of Shi and Xia, which dealt with interactive bi-level multi-objective decision-making problems, with some modifications in assigning satisfactoriness to each objective function in all the levels of the TL-MODM problem.

TL;DR: In this paper, the authors propose an approximation method to generate the set of Pareto solutions of bi-criteria convex optimization problems by fitting a hyper-ellipse to a very small number of pareto points.

TL;DR: In this article, it was shown that the concept of balance points introduced by Galperin (Ref. 1) is equivalent to Pareto optimality, and that balance points are equivalent to balance points in the sense that the balance points can be replaced by balance points.

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.

TL;DR: In this paper, the authors present a classification of MADM methods by data type and propose a ranking method based on the degree of similarity of the MADM method to the original MADM algorithm.

Abstract: Many of the complex problems faced by decision makers involve multiple conflicting objectives. This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe his true feelings in order to make those critically important, vexing trade-offs between incommensurable objectives. The theory is illustrated by many real concrete examples taken from a host of disciplinary settings. The standard approach in decision theory or decision analysis specifies a simplified single objective like monetary return to maximise. By generalising from the single objective case to the multiple objective case, this book considerably widens the range of applicability of decision analysis.