In this thesis, we study the Cyclic Hoist Scheduling Problem (CHSP) in automated electroplating lines, when a mass production must be achieved. The CHSP is characterized by specific constraints related to processing and transport resources. To solve it in a multi-parts context, we first elaborate a 2-degree cyclic model and an associated branch and bound algorithm. Then we extend it to more complex configurations. Then, we develop a dedicated heuristic to find a feasible repetitive sequence of hoist moves that minimizes the cycle time, without a priori fixing the cycle degree. Comparisons with existing algorithms are presented to show the efficiency of the proposed heuristic. To reduce the cycle time, we integrate in the general heuristic an algorithm with a set of Minimum Part Set (MPS) configurations’. This one allows us to find the best order in which jobs should be introduced into the line. Finally, we describe a genetic algorithm approach to find a schedule which can reach the optimal 2-cycle. We finally discuss the interest of those various models, based on the promising results obtained and we provide some perspectives which could be explored.
