Production Scheduling with Capacity-Lot Size and Sequence Consideration

The General Lot-sizing and Scheduling Problem (GLSP) is a common problem found in continuous production planning. This problem involves many constraints and decisions including machine capacity, production lot-size, and production sequence. This study proposes a two-phase algorithm for solving large-scale GLSP models. In Phase 1, we generate patterns with a specific batch size and capacity and in Phase 2, based on the patterns selected in Phase 1, we optimize the production allocation. Additionally, the external supplies are included in the formulation to reflect the real situation in business with limited resources. In this work, the justification of the formulation is based on the ability of solving and calculation time. The proposed formulation was tested on eight scenarios. The results show that the proposed formulation is more tractable and is easier to solve than the GLSP.The General Lot-sizing and Scheduling Problem (GLSP) is a common problem found in continuous production planning. This problem involves many constraints and decisions including machine capacity, production lot-size, and production sequence. This study proposes a two-phase algorithm for solving large-scale GLSP models. In Phase 1, we generate patterns with a specific batch size and capacity and in Phase 2, based on the patterns selected in Phase 1, we optimize the production allocation. Additionally, the external supplies are included in the formulation to reflect the real situation in business with limited resources. In this work, the justification of the formulation is based on the ability of solving and calculation time. The proposed formulation was tested on eight scenarios. The results show that the proposed formulation is more tractable and is easier to solve than the GLSP

Optimal planning and feedstock-mix selection for multiproduct polymer production

In this paper, we describe a nonlinear programming model to determine the optimal balance of feedstocks to manufacture multiple polymer grades in a polypropylene production facility. The main units of the process are a distillation column and a polymerization reactor, for which accurate short-cut process models were developed. Both a single and multiple product formulations are presented. The proposed models seek to maximize the plant throughput while minimizing the production costs. The possibility of adding extra production is also considered. The formulations are applied to several case studies, both to analyze the performance of the model and to illustrate its potential economic impact. The trade-off between feedstocks costs and production rates is analyzed by solving the multiple-product model with different time horizons. An annualized-slate long term case study is presented. The proposed formulation with a user-friendly interface has been deployed to assist with commercial and operation decisions at the plant.The authors would like to acknowledge the financial support received from Braskem America and the Center for Advanced Process Decision Making (CAPD)