Evolutionary and adaptive strategies for efficient search across whole system engineering design hierarchies

Abstract

Evolutionary and Adaptive strategies (ES & AS) for diverse multilevel search across a preliminary, whole-system design hierarchy defined by discrete and continuous variable parameters are described. Such strategies provide high-level decision support when integrated with preliminary design software describing the major elements of an engineering system. Initial work involving a Structured Genetic Algorithm (stGA) with appropriate mutation regimes to encourage search diversity is described and preliminary results are presented. The shortcomings of the stGA approach are identified and alternative strategies are introduced. A dual agent strategy (GAANT) involving elements of an ant colony search and an evolutionary search concurrently manipulating the discrete and continuous variable parameter sets is presented. Appropriate communication between the two search agents results in a more efficient search across the hierarchy than that achieved by the stGA, while also simplifying the chromosomal representation. This simplification allows the further development of the preliminary design hierarchy in terms of complexity. The technique therefore represents a significant contribution to configuration design where multilevel, mixed discrete/continuous parameter design problems can be prevalent.