Hybrid genetic algorithms with dispatching rules for unrelated parallel machine scheduling with setup time and production availability

We study unrelated parallel machine scheduling with setup and production availability.We derive a mixed integer programming model for the problem.We propose hybrid genetic algorithms (HGAs) with three dispatching rules.We evaluate the performances of the GAs using randomly generated examples. This article considers the unrelated parallel machine scheduling problem with sequence- and machine-dependent setup times and machine-dependent processing times. Furthermore, the machine has a production availability constraint to each job. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines to minimize the total completion time. To solve the problem, a mathematical model for the optimal solution is derived, and hybrid genetic algorithms with three dispatching rules are proposed for large-sized problems. To assess the performance of the algorithms, computational experiments are conducted and evaluated using several randomly generated examples.