Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in ...

In this paper we further investigate the problem of finding nadir criterion values (minimum criterion values over the nondominated set) in multiple objective linear programming. Although easy to ...

Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is optimization. According to Somani, every breakthrough in the field—from ...