To promote the green transformation and development of manufacturing enterprises, and aiming at the collaborative optimization of IPPS and multi-source energy supply, this paper proposed a novel multi-verse optimization algorithm. Through the improved operations of embedding the sub-population fusion initialization strategy, the NSGA-Ⅱ mutation strategy and the disturbance strategy of external files, the algorithm expanded the individual population diversity, developed new search ranges, also improved the optimization performance and the quality of Pareto solutions. The multi-energy consumption comparative experiments verified the multi-source energy supply system could effectively improve the proportion of renewable energy consumption and help the manufacturing enterprises achieve the goal of energy conservation and emission reduction. The algorithms comparison experiments show the effectiveness, feasibility and competitiveness of the novel multi-verse optimization algorithm for solving the problem of IPPS and multi-source energy supply collaborative optimization for manufacturing enterprises.

[2023-04-19] Accepted Paper /doc/2023.02.0033/v1

[2023-09-05] Printed Article /doc/2023.02.0033/v2