Abstract
This paper studies the problem of production scheduling in a company belonging to the apparel industry, where textile labels are manufactured through the process of thermal transfer. The problem is modelled as a flexible flowshop with two stages. The objectives are the maximisation of system productivity (or minimisation of makespan) and the minimisation of the number of production orders with late delivery. This paper proposes a scheduling procedure based on a bi-objective genetic algorithm. An experimental study was performed using real data from the enterprise. Since validation results showed the efficiency and effectiveness of the proposed procedure, a decision-aid tool is designed. The algorithm is implemented at the enterprise and allows improved key performance metrics.
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