Abstract:

Equipment products with complex process routes often have decision variables in their production system design that are coupled and affect with each other, affecting the final batch production cost of the product and forming a complex combinatorial optimization problem. In this regard, a complex product batch production routing optimization model based on dynamic cost convolution is proposed. The proposed model considers that there may be multiple production design options at each node of the complex product process routing, and each option corresponds to different production inputs and batch efficiency. The goal is to minimize the batch production cost of the final delivered product and output the production system design and cost convolution routing. At the same time, a mixed integer programming model is established, and by implementing controllable precision linearization on the nonlinear components in the model, the model is transformed into a linear model that can be optimally solved. Finally, small, medium, and large-scale experimental examples are designed for a certain continuous production industry to verify the feasibility, rationality, and solution efficiency of the proposed model.

Key words: batch production cost, cost convolution, routing optimization, optimization model