Previous researchers have made impressive strides in developing algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world
applications. However, most MOEAs based on Pareto-dominance handle many-objective …

Decomposition is a well-known strategy in traditional multiobjective optimization. However,
the decomposition strategy was not widely employed in evolutionary multiobjective …

We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for
computationally expensive optimization problems with more than three objectives. The …

Decomposition via scalarization is a basic concept for multiobjective optimization. The
weighted sum (WS) method, a frequently used scalarizing method in decomposition-based …

CONTENTS 3.1 Introduction.................................................... 146 3.2 MO
Basics..................................................... 1463.2. 1 Principles of MO............................................ 147 …

Real-world optimization problems typically involve multiple objectives to be optimized
simultaneously under multiple constraints and with respect to several variables. While multi …

This paper presents a meta-objective optimization approach, called Bi-Goal Evolution
(BiGE), to deal with multi-objective optimization problems with many objectives. In multi …

Multi-objective optimization has been adopted in many engineering problems where a set of
requirements must be met to generate successful applications. Among them, there are the …

Interactive multiobjective optimization (IMO) aims at finding the most preferred solution of a
decision maker with the guidance of his/her preferences which are provided progressively …