MILP Optimization Models for Short-term Scheduling of Batch Processes

Book Chapter

Authorship

MENDEZ, CARLOS ALBERTO ; Grossmann, Ignacio E. ; Harjunkoski, Iiro ; Fahl, Marco

Date

2008

Publishing House and Editing Place

Wiley-VCH

Book

Logistic Optimization of Chemical Production Processes (pp. 163-184)
Wiley-VCH

ISBN

978-3-527-30830-9

Summary Information provided by the agent in SIGEVA

As there has been a large number of promising developments to the short-term scheduling of batch plants in the last 20 years, the main goal of this work is to provide a general classification of batch scheduling problems and an up-to-date review of the state-of-the-art of this important area. Main features, strengths and limitations of the existing mixed integer linear programming (MILP) optimization techniques will be examined through this paper. We first present a general road-map for schedul... As there has been a large number of promising developments to the short-term scheduling of batch plants in the last 20 years, the main goal of this work is to provide a general classification of batch scheduling problems and an up-to-date review of the state-of-the-art of this important area. Main features, strengths and limitations of the existing mixed integer linear programming (MILP) optimization techniques will be examined through this paper. We first present a general road-map for scheduling problems of batch plants as well as for the available optimization models. Subsequently, a discussion of modeling aspects of representative MILP models is introduced for both discrete and continuous time models. A comparison of effectiveness and efficiency is presented for discrete- and continuous-time models using a benchmark example taken from the literature. Finally, we draw some general conclusions and point out directions for future research.