Energy-Efficient M-Machine Flow Shop Scheduling Under Time-Of-Use Tariffs

Abstract

The objective of this project is to create and incorporate systematic solutions to the m machine flow shop scheduling problem under a 'Time of Use' tariff, with an available makespan for a typical manufacturing process. The solution is formulated using Mixed Integer Linear Programming (MILP) and a general-purpose metaheuristic approach. A small-scale solution for two-machine flow shop scheduling will initially be generated by running the MILP model in CPLEX. The Particle Swarm Optimization (PSO) heuristic is then applied to solve this NP-hard issue using Python, hence increasing the solution's applicability on a broader scale. Ultimately, a range of scenarios will be developed and implemented to accomplish validation and verification. The findings demonstrate that the suggested remedy is successful in addressing the mentioned issues and has the potential to significantly advance this sector.