An Expanded Database Structure for a Class of Multi-period, Stochastic Mathematical Programming Models for Process industries

Narain Gupta, Goutam Dutta and Robert Fourer

No WP2013-12-05, IIMA Working Papers from Indian Institute of Management Ahmedabad, Research and Publication Department

Abstract: We introduce a multiple scenario, multiple period, optimization-based decision support system (DSS) for strategic planning in a process industry. The DSS is based on a two stage stochastic linear program (SLP) with recourse for strategic planning. The model could be used with little or no knowledge of Management Sciences. The model maximizes the expected contribution (to profit), subject to constraints of material balance, facility capacity, facility input, facility output, inventory balance constraints, and additional constraints for non-anticipativity. We describe the database structure for the stochastic linear programming (SLP) based DSS in contrast to the deterministic linear programming (LP) based DSS. In the second part of this paper, we compare a completely relational database structure with a hierarchical one on multiple criteria. We demonstrate that by using completely relational databases, the efficiency of model generation can be improved by 60% in comparison to hierarchical databases.

Date: 2013-12-24
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Persistent link: https://EconPapers.repec.org/RePEc:iim:iimawp:12791

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