Genetic engineering versus natural evolution genetic algorithms with deterministic operators

摘要

Genetic algorithms (GA) have several important features that predestinate them to solving design problems. Their main disadvantage is however can excessively long run-time to deliver satisfactory resuls for large instances of complex design problems. SThe main aim of this paper is to demonstrate that the effective and efficient application of the GA concept to the design problem solving requires substitution of the basic GA's natural evolution by the genetic engineering (GE), to propose and discuss the conept of a genetic engineering algorithm (GEA), and to show how to apply the GEA for solving the synthesis problems. In the paper, an effective and efficient GE scheme is proposed and applied for solving an important design problem: the minimal input support problem (MISP). Our GEA produces in almost all cases the strictly optimal results and realizes the best trade-off between the effectiveness and efficiency. The experimental results clearly demonstrate that the proposed GE sheme is suitable for solving the design problems and its appolication results in very effective and efficient genetic engineering algorithms