改进教学优化算法求解执行器配置与生产调度协同优化问题OA

In the practical flexible job-shop,the efficient collaboration between end-effector allocation and production scheduling benefits providing global decision-making,thus facilitating the flexibility of the workshop.To address the collaborative optimization problem of end-effector allocation and production scheduling,a mixed-integer programming model is constructed to minimize the comprehensive production cost and makespan,enabling the accurate solution of small-scale problems via Gurobi.In addition,a dual-stage discrete teaching-learning-based optimization algorithm is proposed,incorporating a distance-based adaptive adjustment strategy for learning coefficient and an improved neighborhood search based on critical operation movement to facilitate efficiency and objective balancing.Through simulation experiments,the superiority of the proposed collaborative optimization method and the effectiveness of the proposed algorithm are analyzed and validated.