Journal ArticleDOI
The weighted sum method for multi-objective optimization: new insights
TLDR
This paper investigates the fundamental significance of the weights in terms of preferences, the Pareto optimal set, and objective-function values and determines the factors that dictate which solution point results from a particular set of weights.Abstract:
As a common concept in multi-objective optimization, minimizing a weighted sum constitutes an independent method as well as a component of other methods. Consequently, insight into characteristics of the weighted sum method has far reaching implications. However, despite the many published applications for this method and the literature addressing its pitfalls with respect to depicting the Pareto optimal set, there is little comprehensive discussion concerning the conceptual significance of the weights and techniques for maximizing the effectiveness of the method with respect to a priori articulation of preferences. Thus, in this paper, we investigate the fundamental significance of the weights in terms of preferences, the Pareto optimal set, and objective-function values. We determine the factors that dictate which solution point results from a particular set of weights. Fundamental deficiencies are identified in terms of a priori articulation of preferences, and guidelines are provided to help avoid blind use of the method.read more
Citations
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Rapid Variable-Resolution Parameter Tuning of Antenna Structures Using Frequency-Based Regularization and Sparse Sensitivity Updates
TL;DR: In this article , a frequency-based regularization is employed to facilitate the relocation of antenna operating parameters to their target values, which increases the chances of identifying a satisfactory design under challenging conditions (e.g., poor-quality starting point).
Journal ArticleDOI
A relax-and-fix Pareto-based algorithm for a bi-objective vaccine distribution network considering a mix-and-match strategy in pandemics
Dissertation
A modified mean-variance-conditional value at risk model of multi-objective portfolio optimization with an application in finance
TL;DR: A hybrid optimization algorithm which utilizes a classical approach, WSM and a meta-heuristic approach, ACO to solve an MVC model of portfolio optimization, which can be used in managing diverse investment portfolio.
Journal ArticleDOI
Multiobjective Pinch Analysis for Resource Conservation in Constrained Source–Sink Problems
TL;DR: In this paper, the authors aim to conserve resource in manufacturing and process industries to fulfill environmental discharge and societal responsibilities, and propose a resource conservation strategy for the manufacturing and processing industries.
References
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Journal ArticleDOI
A Scaling Method for Priorities in Hierarchical Structures
TL;DR: A method of scaling ratios using the principal eigenvector of a positive pairwise comparison matrix is investigated, showing that λmax = n is a necessary and sufficient condition for consistency.
Book
Nonlinear Multiobjective Optimization
TL;DR: This paper is concerned with the development of methods for dealing with the role of symbols in the interpretation of semantics.
Journal ArticleDOI
Survey of multi-objective optimization methods for engineering
R.T. Marler,Jasbir S. Arora +1 more
TL;DR: A survey of current continuous nonlinear multi-objective optimization concepts and methods finds that no single approach is superior and depends on the type of information provided in the problem, the user's preferences, the solution requirements, and the availability of software.
Book
Multiple Criteria Optimization: Theory, Computation, and Application
TL;DR: 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.
Book
Multiple Objective Decision Making ― Methods and Applications: A State-of-the-Art Survey
Ching-Lai Hwang,Kwangsun Yoon +1 more
TL;DR: On MADM Methods Classification.