Annals of Operations Research

, Volume 139, Issue 1, pp 131-162

First online:

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

  • Christodoulos A. FloudasAffiliated withDepartment of Chemical Engineering, Princeton University Email author 
  • , Xiaoxia LinAffiliated withDepartment of Chemical Engineering, Princeton University

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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.


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