A novel constraint programming model for large-scale scheduling problems in multiproduct multistage batch plants: Limited resources and campaign-based operation

• An efficient constraint programming model addressing scheduling problems is proposed.
• Several features found in actual industrial environments are taken into account.
• The approach deals with large-scale problems involving multiple-batch orders.
• A campaign operating mode and limits on the batch number per campaign can be chosen.
• Assignment, sequencing and timing decisions are made in an integrated way.

This contribution introduces an efficient constraint programming (CP) model that copes with large-scale scheduling problems in multiproduct multistage batch plants. It addresses several features found in industrial environments, such as topology constraints, forbidden product-equipment assignments, sequence-dependent changeover tasks, dissimilar parallel units at each stage, limiting renewable resources and multiple-batch orders, among other relevant plant characteristics. Moreover, the contribution deals with various inter-stage storage and operational policies. In addition, multiple-batch orders can be handled by defining a campaign operating mode, and lower and upper bounds on the number of batches per campaign can be fixed. The proposed model has been extensively tested by means of several case studies having various problem sizes and characteristics. The results have shown that the model can efficiently solve medium and large-scale problems with multiple constraining features. The approach has also rendered good quality solutions for problems that consider multiple-batch orders under a campaign-based operational policy.