Data-driven oriented optimization of resource allocation in the forging process using Bi-objective Evolutionary Algorithm

摘要

Resource allocation in the forging process of the steel production industry is an important element of the material supply in upstream processes, and the subsequent processing of semi-finished products downstream. However, the existing literature rarely discusses issues related to this problem. In this study, the information flow is built by referring to specifications and process logic, which is a kind of pre-processing in data analysis flow in order to break the initial barrier of resource allocation in forging. In addition, Bi-objective Evolutionary Algorithm (BOEA) is proposed to optimize the resource allocation in the forging process. Using the built information flow, the available multiple forging process resources can be effectively connected, and information of available resource combinations can be established for orders. Since real users have preferences for different objectives in practice, experiment results show that the proposed BOEA can deal with these preferences by effectively optimizing both the remnants (the remaining materials) and the execution cost, and the profit contribution is also proved by effective cost savings.