Genetic algorithms for single machine family scheduling problems with maximum lateness and completion time

Abstract

Single machine family scheduling problem with family setup times is a combinatorial optimisation problems where jobs are partitioned into families and setup time is required between these families. Genetic algorithms using an optimised crossover operator designed by an undirected bipartite graph are proposed for solving the problems of minimising the maximum lateness and minimising the total weighted completion time respectively. Computational experiments are conducted to assess the efficiency of the proposed algorithms compared to other variants of genetic algorithms. Computational results of each problem showed that the proposed algorithms are able to generate better quality solutions compared to others.