This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
This paper presents ObjRecombGA, a genetic algorithm framework for recombining related programs at the object file level. A genetic algorithm guides the selection of object file...
This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ‘Ra’ and build time ‘T’, for object manufac...
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. ...
We present an algorithmic approach to solving the problem of chromatic entropy, a combinatorial optimization problem related to graph coloring. This problem is a component in algor...
A fundamental aspect of many evolutionary approaches to synthesis of complex systems is the need to compose atomic elements into useful higher-level building blocks. However, the ...
This paper presents the virtual gene genetic algorithm (vgGA) which is a generalization of traditional genetic algorithms that use binary linear chromosomes. In the vgGA, tradition...
The problem of searching for a walker that wants to be found, when the walker moves toward the helicopter when it can hear it, is an example of a two sided search problem which is ...
Abstract. A hybrid genetic algorithm is proposed for the sequential ordering problem. It is known that the performance of a genetic algorithm depends on the survival environment an...
Abstract. As a preprocessing for genetic algorithms, static reordering helps genetic algorithms effectively create and preserve high-quality schemata, and consequently improves th...