Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey

By C. Hwang. 1979

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

The Promise and Peril of Human Evaluation for Model Interpretability (2017, background): “• Multi-objective loss functions – Optimization of a multi-objective loss function becomes difficult when nontrivial [10, 13, 5, 1].”
A Survey on Neural Architecture Search (2019, background): “Another approach to handle multiple fronts lies in the formalism of multi-objective optimization problem (Hwang and Masud, 2012) defined as max α∈A f1 (α) , f2 (α) , . . . , fn (α) .”
Multiple criteria facility location problems: A survey (2010, background): “[18] and Hwang and Masud [17] to learn more about pure MODM and referred to Hwang and Yoon [14] to gain knowledge about pure MADM.”
The weighted sum method for multi-objective optimization: new insights (2010, background): “Many researchers have, however, developed systematic approaches to selecting weights, surveys of which are provided by Eckenrode (1965), Hobbs (1980), Hwang and Yoon (1981) , and Voogd (1983).”
Techniques for highly multiobjective optimisation: some nondominated points are better than others (2007, methodology): “s induced by these two methods are the same. Finally, we note that methods very similar to those discussed here have been long considered in the field of multicriteria decisionmaking (MCDM), e.g. see [18]. In that area, however, the emphasis is on finding compromise points, rather than finding appro”
APPLICATIONS OF MULTIOBJECTIVE OPTIMIZATION IN CHEMICAL ENGINEERING (2000, background): “These are described in several textbooks (Zeleny, 1974, 1982; Cohon, 1978; Hwang and Masud, 1979; Steuer, 1986; Haimes et al., 1975, 1990; Chankong and Haimes, 1983; Goicoechea et al., 1982) and research and review articles (Geoffrion, 1967a-c; Geoffrion et al.”
Zebra Optimization Algorithm: A New Bio-inspired Optimization Algorithm for Solving Optimization Algorithm (2022, background): “Each optimization problem is determined by its decision variables, constraints, and objective function [1].”
Understanding knee points in bicriteria problems and their implications as preferred solution principles (2011, background): “…cases, the front obtained by the Pareto-optimal solutions is such that the choice of a single preferred solution is not straightforward and a multi-criteria decision-making methodology is needed to choose a single preferred solution systematically (Hwang and Masud 1979, Chankong and Haimes 1983).”
Selecting Plant Location via a Fuzzy TOPSIS Approach (2002, methodology): “The technique for order preference by similarity to an ideal solution (TOPSIS) was initiated by Hwang and Yoon [ 8 ].”