Makespan optimization in the fl exible Job Shop problem with transportation constraints using Genetic Algorithms (2019)
We solved the Flexible Job Shop Scheduling Problem (FJSSP) with transportation constraints in order to minimize the makespan by sequencing and assigning machines. A bibliographic review was made in order to guide the methodology to be used. From there, we approached the problem with a genetic algorithm. We validated its eff ectiveness by comparing the results obtained with diff erent instances proposed in the literature. The results obtained show that the proposed genetic algorithm is efficient in the diff erent classic Job Shop confi gurations tested. The algorithm is able to find very approximate solutions to the best found to date for the Flexible Job Shop Scheduling Problem with transportation constraints.