: The Shifting Balance Genetic Algorithm (SBGA) is a pluggable module for a GA (or any other Evolutionary Algorithm) based on a modification of Sewall Wright's shifting balanc...
Abstract- The main purpose of this work is to measure the effect of bargaining players’ information completeness on agreements in evolutionary environments. We apply Co-evolution...
- It is widely believed that greater initial population diversity leads to improved performance in genetic algorithms. However, this assumption has not been rigorously tested previ...
Abstract— This paper presents a genetic algorithmic approach for finding efficient paths in directed graphs when optimizing multiple objectives. Its aim is to provide solutions...
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...