# Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications

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## Abstract

This paper reviews the advances of mixed-integer linear programming (MILP) based approaches for the scheduling of chemical processing systems. We focus on the short-term scheduling of general network represented processes. First, the various mathematical models that have been proposed in the literature are classified mainly based on the time representation. Discrete-time and continuous-time models are presented along with their strengths and limitations. Several classes of approaches for improving the computational efficiency in the solution of MILP problems are discussed. Furthermore, a summary of computational experiences and applications is provided. The paper concludes with perspectives on future research directions for MILP based process scheduling technologies.

## Keywords

chemical process scheduling mixed-integer linear programming (MILP) discrete-time model continuous-time model branch and bound## Preview

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## References

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