(714b) Multistage Stochastic Optimization with Recourse in Batch Plant Scheduling | AIChE

(714b) Multistage Stochastic Optimization with Recourse in Batch Plant Scheduling

Authors 

Sun, L. - Presenter, Dalian University of Technology
Wang, F. - Presenter, Dalian University of Technology

Batch processes
are the prevalent mode of production for the manufacture of many types of chemicals
products, particularly those production processes or the demand patterns are
likely to change. During the last decade, the problems of short-term batch
plant scheduling became very important in industrial plant operations, and quantities
of work have been done on them, in which three types of time domain
representations (discrete-time, continuous-time, event point) and two kinds of
batch process representations (state-task network (STN), resource-task network
(RTN)) have been proposed. Most of the work has been assumed as deterministic approaches.
However, in real plants, parameters such as raw material availability, costs, processing
times, and market requirements vary with respect to time and are often subject
to unexpected deviations, therefore, the consideration of these uncertain
factors in scheduling becomes of great importance in preserving plant
feasibility and viability during operations.

There has been increasing
interest in the development of probabilistic models to copy explicitly with
uncertainties. Straub and Grossmann proposed the idea of the stochastic
flexibility index to evaluate the effect of uncertainty quantitatively. Ierapetritou
and Pistikopoulos presented a two-stage stochastic programming formulation for
the batch plant design and operations. Sand et al. proposed an algorithm to
approximate the performance of an ideal online scheduler for a multi-product
batch plant. Balasubramanian and Grossmann proposed an approximation strategy
based on the solution of a series of a two-stage model within a
shrinking-horizon approach to reduce problem sizes and computational time.

In this work, efforts
were made on the multistage batch plants scheduling under demand uncertainty and
recourse strategy was employed to obtain the optimal schedule. The multiperiod problem
was firstly reformulated as a two-period problem and optimized by the strategy
of the stochastic programming with recourse. An initial feasible solution was
obtained and can be introduced to the original multistage problem to improve
the first stage decision. Similarly, the scheduling problem can be solved in a
reduced scope with resource until the whole scheduling was achieved. An example
will be presented to illustrate the validity and effectiveness of the proposed
approach.

Keywords: multistage, scheduling, recourse