— Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the i...
In this Chapter we present the modification of a Differential Evolution algorithm to solve constrained optimization problems. The changes include a deterministic and a self-adapti...
— Regulatory networks are complex networks. This paper addresses the challenge of modelling these networks. The Boolean representation is chosen and supported as a representation...
Cristina Costa Santini, Gunnar Tufte, Pauline C. H...
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
— By dividing the multiobjective optimization of the decision space into several small regions, this paper proposes multi-objective optimization algorithm based on sub-regional s...
— A hyperheuristic is a high level problem solving methodology that performs a search over the space generated by a set of low level heuristics. One of the hyperheuristic framewo...
— Concurrent process-oriented programming is a natural medium for simulating complex systems, particularly systems where many simple components interact in an environment (which ...
Fiona A. C. Polack, Paul S. Andrews, Adam T. Samps...
— This paper presents a critical analysis of the Pareto-Following Variation Operator (PFVO) when used as an approximation method for Multiobjective Evolutionary Algorithms (MOEA)...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...