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

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 literat...

Full description

Saved in:
Bibliographic Details
Published in:Annals of operations research 2005-10, Vol.139 (1), p.131-162
Main Authors: Floudas, Christodoulos A., Lin, Xiaoxia
Format: Article
Language:English
Subjects:
Algorithms
Chemical engineering
Chemical process industries
Linear programming
Manufacturing
Mathematical models
Mathematical programming
Operations research
Optimization techniques
Production planning
Recipes
Schedules
Scheduling
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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. [PUBLICATION ABSTRACT]
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-005-3446-x