Energy-Efficient Distributed Welding Shop Scheduling Based on Multi-Objective Seagull Algorithm

For the energy-efficient distributed welding shop scheduling problem, focusing on the scheduling of production in a distributed welding shop, a mathematical model is established with the objective of minimizing the makespan and total energy consumption. In order to solve this optimization problem, an improved multi-objective seagull algorithm (IMOSOA) is proposed. The algorithm introduces three main enhancements: designing a weight matrix based on multiple critical paths to update the number of welders allocated to each job, redesigning the discretization operations of the multi-objective seagull algorithm according to the characteristics of distributed welding shop, and incorporating a Pareto front selection strategy. This strategy uses a new crowding distance calculation to resolve cases where non-dominated solutions at the same dominance level have equal crowding distances, thereby improving the next generation of solutions. These improvements not only reduce the maximum completion time and total energy consumption but also enhance search efficiency. Finally, the IMOSOA is compared with other algorithms under different scale examples, and the results show that the energy consumption is at least 11.7% lower than that of the comparison algorithm, which verifies the superiority of the IMOSOA.