A multi-objective genetic algorithm to solve a single machine scheduling problem with setup-times

Abstract

The objective of this research is to study the one machine scheduling problem with setup-times. Two objectives were considered; the completion time and the total weighted tardiness. Only the static version of the problem was treated. The problem is NP-hard and not approximable. We proposed a multi-objective genetic algorithm with new crossover operators to solve the problem. To validate the algorithm, we conducted an intensive experimental study, which showed that the new operators allowed the genetic algorithm to generate Pareto optimal solutions close to many developed lower bounds.