This paper provides an overview of developments on termination conditions in evolutionary
algorithms (EAs). It seeks to give a representative picture of the termination conditions in …

Over the last decades, evolutionary algorithms have been extensively used to solve multi-
objective optimization problems. However, the number of required function evaluations is …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

The use of multi-objective evolutionary algorithms for solving black-box problems with
multiple conflicting objectives has become an important research area. However, when no …

Multiobjective evolutionary algorithms evolve a population of solutions through successive
generations toward the Pareto-optimal front (POF). One of the most critical questions faced …

Multi-objective (or multi-criteria) optimization (MOO) is useful for gaining deeper insights into
trade-offs among objectives of interest and then selecting one of the many optimal solutions …

This study focuses on the shift from traditional farming methods, reliant on farmer intuition
and manual processes, to modern, automated approaches crucial for Thailand's agricultural …

This paper presents a combinatorial multiobjective optimization methodology to address
diversification of investment in portfolios consistent with the market practices, using a …

Software architecture optimization aims to enhance non-functional attributes like
performance and reliability while meeting functional requirements. Multi-objective …

This paper proposes a new stopping criterion for decomposition-based multi-objective
evolutionary algorithms (MOEA/Ds) to reduce the unnecessary usage of computational …