Energy-efficient multi-objective flexible manufacturing scheduling

This paper presents a novel scheduling of a resource-constrained Flexible Manufacturing System (FMS) with consideration of the following sub-problems: (i) machine loading and unloading, (ii) manufacturing operation scheduling, (iii) machine assignment, and (iv) Automated Guided Vehicle (AGV) scheduling. In the proposed model, both the AGV and machinery are considered as the required resources. Energy efficiency of AGVs has been studied in order to improve environmental sustainability in terms of a linear function, which is based on load and distance, accordingly. Because of the NP-hard characteristics of the problem, a modified multi-objective particle swarm optimization (MMOPSO) has been developed for solving the model and compared with the classic version of the multi-objective particle swarm optimization (MOPSO) algorithm in terms of five performance metrics. Finally, the results are evaluated by the application of a multi-criteria decision-making (MCDM) algorithm according to which the MMOPSO outperforms the MOPSO. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes a novel scheduling approach for a resource-constrained Flexible Manufacturing System (FMS) by considering energy efficiency of AGVs and using a modified multi-objective particle swarm optimization algorithm to solve the problem, which outperforms the classic version of the algorithm according to the results.