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 …

Dominance In the single-objective optimization problem, the superiority of a solution over other solutions is easily determined by comparing their objective function values In multi-objective optimization …

Multiobjective optimization is defined as a mathematical optimization approach that involves simultaneously optimizing two or more conflicting objective functions, particularly in scenarios where …

Why multiobjective optimization ? While multidisciplinary design can be associated with the traditional disciplines such as aerodynamics, propulsion, structures, and controls there are also the lifecycle …

Multi-objective optimization (MOO) is a technique to find the best solution when multiple conflicting objectives or criteria must be simultaneously satisfied. Unlike traditional optimization problems where …

May 31, 2018 · Finally, it highlights recent important trends and closely related research fields. The tutorial is intended for readers, who want to acquire basic knowledge on the mathematical …

Learn how to minimize multiple objective functions subject to constraints. Resources include videos, examples, and documentation.

This paper examines algorithmic methods, applications, trends, and issues in multi-objective optimization research. This exhaustive review explains MOO algorithms, their methods, and their …

Three different ways of solving multi-objective optimization problems were introduced, which all effectively convert the problem to a single-objective optimization problem.

Dec 16, 2025 · A recent study demonstrates the applicability of quantum computers for multi-objective optimization, bringing quantum computing a step closer towards practical applications.