NSGA-II-based Multi-Objective Optimization for a Flexible Flow Shop No-Wait Problem with Unrelated Parallel Machines

Scheduling production in environments with multiple stages, heterogeneous machines, and specific operational constraints directly impacts production efficiency. In food industries, sequencing and allocation decisions also influence the use of raw materials. This paper investigates a Flexible Flow Shop Scheduling problem with unrelated parallel machines in a dairy industry, considering sequence-dependent setups and no-wait constraints. A multiobjective approach based on the Non Dominated Sorting Genetic Algorithm II (NSGA-II) is proposed, aiming to maximize the accumulated raw material yield and minimize the total processing time. The method was evaluated in eight real instances. The results indicate the generation of promising non-mastered solutions with low computational time, offering relevant alternatives for production planning.