A New Genetic Algorithm Approach to Optimize the Workload Balance in a Case Study of a Footwear Industry

Heuristic optimization methods, such as genetic algorithms (GA), have shown promising results for solving problems involving the balancing of flexible manufacturing systems. Therefore, this work proposes a new genetic algorithm approach to optimize the workload balance and number of delayed tasks in an application case of a footwear industry. Focusing on the development of a GA applied to an existing framework, a linear chromosome representation was used to load the manufacturing system information to the genetic operators responsible for the optimization process. A mathematical method is proposed with the aim to minimize the unbalance of the production sector, to validate the method constructed, the results were tested in comparison with other authors works. After it was possible to assemble a layout for the studied industry and contrast it with the factory current configuration. The results of 40% unbalance improved to 22% show that the standard GA obtained a better balance.