Energy Saving in Single-Machine Scheduling Management: An Improved Multi-Objective Model Based on Discrete Artificial Bee Colony Algorithm

Green manufacturing, which takes environmental effect and production benefit into consideration, has attracted increasing concern with the target of carbon peaking neutrality proposed. As a critical process in manufacturing system, shop scheduling is also an important method for enterprises to achieve green manufacturing. Therefore, it necessary consider both benefits objectives scheduling, are symmetrical equally important. In addition, noise pollution become issue that cannot be ignored processes, but been paid less attention previous studies. Thus, MODABC algorithm, optimization simultaneously minimizing lead-time/tardiness cost job-shop emission proposed this paper. We designed discrete permutation-based two-layer encoding mechanism generate initial population. Then, three crossover methods were used perform nectar update operations employed bee search phase, neighbourhood structures improve onlooker operations. Finally, algorithm was compared other classical MOEAs. The results demonstrate can provide non-dominated solution set good convergence distribution, show significant superiority solving single-machine multi-objective problems.