Research on Many-Objective Scheduling Optimization Method for the Large-Scale Hybrid System

Abstract

For the many-objective collaborative optimization problem of high performance alloy casting manufacturing process, how to achieve high efficiency, low energy consumption and intelligent scheduling process is an urgent problem to be solved. Firstly, a multi-objective pro-duction scheduling model of the whole process was established according to the production characteristics, process flow and production constraints. Meanwhile, a new high-dimensional multi-objective strong dominant optimization algorithm was proposed to solve the production scheduling model of high-performance alloy melting casting production line. The proposed algorithm is designed by combining strong domination algorithm and large neighborhood search algorithm. The proposed algorithm method implements deep exploration of solution space through cyclic destruction-repair operation. Its dynamic neighborhood characteristics can effectively escape the local optimal. Based on the industrial data set of alloy casting production line, the performance of the model and the proposed algorithm are tested. Experimental results substantiate the effectiveness and comparative advantages of the many-objective scheduling model and the proposed algorithm method.