Hybrid estimation of distribution and tabu search algorithm for flexible job shop scheduling problem with multi-resource constraints

As the competition becomes more and more fierce, manufacturing enterprises, in addition to improving production efficiency as much as possible, reducing resource consumption, and improving profitability, also provide customers with personalized, customized products to meet the endless needs of customers to attract customers and compete for more markets. In the actual production process, the time spent in the processing is very little, most of which is consumed in resource allocation and production scheduling, so the development of a good resource management and production scheduling plan is crucial to improve the production efficiency of enterprises and reduce energy consumption costs. This paper proposes a hybrid distribution estimation algorithm and Tabu search (HEDA-TS) algorithm framework to solve the multi-resource constraints flexible job shop scheduling problem with limited auxiliary module replacement times (MRCFJSP-AR). Through the comparison of 15 examples, the superior performance of the HEDA-TS algorithm in solving MRCFJSP-AR with limited module replacement times is verified, and the effectiveness of the multi-population strategy and non-dominated solution memory mechanism is highlighted.