Mixed integer linear programming in process scheduling: modeling, algorithms, and applications

DOI10.1007/s10479-005-3446-xzbMath1091.90055OpenAlexW2026080429MaRDI QIDQ817182

Christodoulos A. Floudas, Xiaoxia Lin

Publication date: 7 March 2006

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-005-3446-x

zbMATH Keywords

branch and bounddiscrete-time modelcontinuous-time modelchemical process schedulingmixed-integer linear programming (MILP)

Mathematics Subject Classification ID

Mixed integer programming (90C11) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Deterministic scheduling theory in operations research (90B35) Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming (90-02)

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Cites Work

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• Assignment and sequencing models for the scheduling of process systems
• A hierarchy of relaxations and convex hull characterizations for mixed- integer zero-one programming problems
• Bayesian heuristic approach to discrete and global optimization. Algorithms, visualization, software, and applications. Incl. 2 disks
• Redefining event variables for efficient modeling of continuous-time batch processing
• Improved Linear Integer Programming Formulations of Nonlinear Integer Problems
• LP-based heuristics for scheduling chemical batch processes
• The Schedule-Sequencing Problem

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