This
work presents a novel approach for enterprise-wide planning
and scheduling problem in paper, pulp and printing industry.
This is essentially a large dimensional *mixed integer nonlinear
optimization* problem. In the current approach it has been systematically
decomposed into the interconnected smaller sub-problems by
using spatial and temporal considerations. Each of these sub-problems
can be solved relatively easily and with less computational
efforts using existing capabilities of the available solvers
and personal computers.

The proposed decomposition has a hierarchical structure,
which strongly relies on the algorithmic approach with
minimal use of heuristics and permits systematic
analysis of the problem at various levels. The *rolling horizon* concept is used
to deal with the dimensionality problem along with the changing future demands
and possible disruptions. The resulting set of large scale sub-problems are
solved using ILOG CPLEX 7.1 Solver. The efficacy of the
proposed solution approach is
evaluated by conducting studies on a large dimensional industrial problem (3200
orders, 5 paper machines and 3 month horizon, about 300,000 variables). The
proposed solution scheme provides satisfactory solutions
to the large scale industrial
problem for multiple scenarios in a reasonable time frame (about 2 to 3 minutes
on 2.4 GHz PIV PC). Thus, the proposed solution scheme can effectively deal
with large dimensional enterprise-wise order allocation,
inventory allocation, run
formation, trimming and pattern sequencing problems in a coordinated fashion.

This project was funded by Honeywell Technology Solution
Laboratory. (HTSL), Bangalore and IIT Bombay team working
on the project consisted of Prof Sachin
Patwardhan (PI), Prof K P Madhavan (Consultant), Mangesh Kapadi and S A Munawar
(project engineers). Also, HTSL, Bangalore and IIT Bombay are in the process
of jointly filing two US patents based on the technology developed.