Genetic Algorithm Integrated with Artificial Chromosomes for Multi-objective Flowshop Scheduling Problems


Recently, a wealthy of research works has been dedicated to the design of effective and efficient genetic algorithms in dealing with multi-objective scheduling problems. In this paper, an artificial chromosome generating mechanism is designed to reserve patterns of genes in elite chromosomes and to find possible better solutions. The artificial chromosome generating mechanism is embedded in simple genetic algorithm (SGA) and the non-dominated sorting genetic algorithm (NSGA-II) to solve single-objective and multiobjective flowshop-scheduling problems, respectively. The single-objective problems are to minimize the makespan while the multi-objective scheduling problems are to minimize the makespan and the maximum tardiness. Extensive numerical studies are conducted and the results indicate that artificial chromosomes embedded with SGA and NSGAII are able to further speed up the convergence of the genetic algorithm and improve the solution quality. This promising result may be of interests to industrial practitioners and academic researchers in the field of evolutionary algorithm or machine scheduling.