
Multi-objective optimization - Wikipedia
Multi-objective is a type of vector optimization that has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives.
Multi-Objective Optimization Problems (MOOP) Involve more than one objective function that are to be minimized or maximized Answer is set of solutions that define the best tradeoff between competing objectives
A new optimization algorithm to solve multi-objective problems
Oct 13, 2021 · Simultaneous optimization of several competing objectives requires increasing the capability of optimization algorithms. This paper proposes the multi-objective moth swarm algorithm, for...
A Comprehensive Review on Multi-objective Optimization
Jul 4, 2022 · This paper briefly explains the multi-objective optimization algorithms and their variants with pros and cons. Representative algorithms in each category are discussed in depth.
A review of multi-objective optimization: Methods and its applications
Aug 29, 2018 · Several reviews have been made regarding the methods and application of multi-objective optimization (MOO). There are two methods of MOO that do not require complicated mathematical equations, so the problem becomes simple. These two …
Constrained multi-objective optimization problems: …
Sep 5, 2024 · Researchers have developed a variety of constrained multi-objective optimization algorithms (CMOAs) to find a set of optimal solutions, including evolutionary algorithms and machine learning-based methods. These algorithms exhibit distinct advantages in solving different categories of CMOPs.
Stochastic multi-objective optimization \Multi-objective methods": they convert the original problem into an approximated deterministic multi-objective one (e.g., using SAA).
In this chapter, we present a brief description of an evolutionary optimization procedure for single-objective optimization. Thereafter, we describe the principles of evolutionary multi-objective optimization. Then, we discuss some salient developments in EMO research.
Constrained Multi-Objective Optimization With Deep …
Mar 28, 2024 · Various constrained multi-objective optimization evolutionary algorithms (CMOEAs) have been developed with the use of different algorithmic strategies, evolutionary operators, and constraint-handling techniques.
A review and evaluation of multi and many-objective optimization ...
Nov 9, 2022 · Multi and many-objective algorithms have a great application in engineering science. This study addresses a complete and updated review of the literature for multi and...