A multiobjective optimization problem involves several conflicting objectives and has a set of
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …

Abstract Chemical Reaction Optimization (CRO) is a recently established metaheuristics for
optimization, inspired by the nature of chemical reactions. A chemical reaction is a natural …

Evolutionary algorithms (EAs) have been widely and successfully applied to solve multi-
objective optimization problems, due to their nature of population-based search. Population …

The potential and effectiveness of the newly developed Pareto-based multiobjective
evolutionary algorithms (MOEA) for solving a real-world power system multiobjective …

DNA computing has efficient computational power, but requires high requirements on the
DNA sequences used for coding, and reliable DNA sequences can effectively improve the …

This study developed a novel model, HGA-SVR, for type of kernel function and kernel
parameter value optimization in support vector regression (SVR), which is then applied to …

This paper reviews the application of multiobjective optimization in the fields of
bioinformatics and computational biology. A survey of existing work, organized by …

Abstract Particle Swarm Optimization (PSO) algorithm is a member of the swarm
computational family and widely used for solving nonlinear optimization problems. But, it …

Recent advances in evolutionary algorithms show that coevolutionary architectures are
effective ways to broaden the use of traditional evolutionary algorithms. This paper presents …

Optimization problems can generally be classified as continuous and discrete, based on the
nature of the solution space. A recently developed chemical-reaction-inspired metaheuristic …