An efficient lexicographic approach to solve multi-objective multi-port fabric dyeing machine planning problem

Abstract

In this study, the fabric dyeing process in a towel manufacturing factory is investigated, focusing on the batching of towel fabric bolts with different quantities and features belonging to different orders in multi-port dyeing machines. This research differs from previous studies in several aspects. Firstly, it is considered three different objectives: total tardiness, total number of washes (sequence-dependent setups), and total machine fixed cost. These objectives have not been simultaneously optimized in previous studies, making our approach unique. Secondly, we adopt a lexicographic optimization approach to prioritize these objectives according to the company’s requirements. This allows to find solutions that are optimal in terms of one objective while satisfying the constraints imposed by the other objectives. Lastly, it is proposed a novel lexicographic multi-objective genetic algorithm, which extends the traditional single-objective genetic algorithm, to effectively solve large-sized problems. Overall, our study not only addresses a real-life problem in the textile industry but also introduces innovative techniques and approaches for optimizing multiple objectives in a scheduling context.