Abstract— In this paper, we present an approach to obstacle avoidance for a group of unmanned vehicles moving in formation. The goal of the group is to move through a partially u...
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Abstract. This paper investigates the sample weighting effect on Genetic Parallel Programming (GPP) that evolves parallel programs to solve the training samples captured directly f...
Finite element analysts and designers need to feel confident in the results of their analyses before sending a product to prototype or production. Mesh discretization can greatly ...
Joseph R. Tristano, Zhijian Chen, D. Alfred Hancq,...
Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs are proposed to overcome the deficiencies of sequential GAs, such as low speed and aptn...
Baowen Xu, Yu Guan, Zhenqiang Chen, Karl R. P. H. ...