Multirecombined evolutionary algorithm inspired in the Selfish Gene theory to face the weighted tardiness scheduling problem

Abstract

In a production system it is usual to stress minimum tardiness to achieve higher client satisfaction. According to the client relevance, job processing cost, and many other considerations a weight is assigned to each job. An important and non-trivial objective is to minimize weighted tardiness. Evolutionary Algorithms have been successfully applied to solve scheduling problems. MCMP-SRI (Multiple Crossover Multiple Parents - Stud Random Immigrants) is a MCMP variant which considers the inclusion of a studbreeding individual in a parent's pool of random immigrants. The Selfish Gene Algorithm proposed by Corno et al. is an interpretation of Darwinian theory given by the biologist Richard Dawkins. In this work we are showing a new algorithm that combines the MCMP-SRI and Selfish Gene approaches. This algorithm is used to face the weighted tardiness problem in a single machine environment. The paper summarizes implementation details and discusses its performance for a set of problem instances taken from the OR-Library. © Springer-Verlag Berlin Heidelberg 2004.