Distributed Energy-Efficient Flexible Manufacturing With Assembly and Transportation: A Knowledge-Based Bi-Hierarchical Optimization Approach

As manufacturing processes continue to evolve, distributed and energy-efficient flexible manufacturing systems have become the central paradigm of intelligent manufacturing. To effectively meet the demands of intricate production scheduling requirements, it is crucial to take into account practical factors, such as two-stage assembly production and finite transportation resources. However, this imposes greater demands on the efficiency of scheduling algorithms. In this paper, a knowledge-based bi-hierarchical optimization algorithm (KBOA) is specially designed for solving the distributed energy-efficient assembly flexible job shop problem with transportation constraints (DEAFJSP-T). The objectives of minimizing makespan and total energy consumption are simultaneously taken into account. The search process of the KBOA is structured into two distinct modes. In the first mode, single-objective searches are conducted along several specified directions. To elevate the overall quality of the population, knowledge-based initialization strategies are employed, tailored for different objectives. Furthermore, the knowledge-based local search is designed to strengthen the exploitation of the KBOA by leveraging the interconnections among subproblems. Incorporating the search results from the first mode, the multi-objective search is conducted based on Pareto dominance in the second stage. Considering the characteristics of the problem, individual cooperation is employed to enhance the search efficiency of the KBOA. Extensive experiments are conducted to assess the performances of the KBOA. The statistical comparisons demonstrate that the KBOA is superior in solving the DEAFJSP-T in terms of efficiency and effectiveness. Note to Practitioners -Drawing inspiration from a real-world case in an electrical machinery equipment factory, we have observed the implementation of distributed energy-efficient flexible manufacturing with assembly and transportation (DEAFJSP-T). In this practical scenario, we must concurrently optimize two conflicting objectives of time and energy consumption, taking into account the intricate coupling relationship among processing, assembly and transportation, and satisfying complex constraints. Traditional scheduling methods often fall short in directly resolving such problems. Consequently, this research holds significant practical application value and academic importance. Given the distinctive nature of the problem, we have introduced a bi-hier