Enterprise-Wide Optimization

Enterprise-wide optimization(EWO) is receiving increasing interest from various process industries for remaining competitive and maintaining their profitability. EWO encompasses the optimization of several operations of an industry such as, production, supply, and distribution. While supply chain optimization (SCO) aims at similar objectives of minimizing operational costs throughout the supply chain, more emphasis is given in SCO on the issues related to logistics and transportation. On the other hand, EWO gives more preference to the production side by focusing on planning, scheduling, and operational control aspects. The very first definition of EWO is provided by Prof. Ignacio Grossmann (CMU), which states:

Enterprise-wide optimization is an area that lies at the interface of chemical engineering (process systems engineering) and operations research. It involves optimizing the operations of supply, manufacturing (batch or continuous), and distribution in a company. The major operational activities include planning, scheduling, real-time optimization, and inventory control.  

EWO promotes integration and information exchange across various decision-making layers (such as, strategic, tactical, and, operational) and across various operational functions (such as, purchase, production, distribution, and sales) of an industry which may also lead to coordinated decision-making across various geographically distributed organizational components (such as, vendors, facilities, and markets). However, coordination and integration among various spatially distributed components of the supply chain as well as temporally varying(different time scales of operations) decision-making layers pose significant modeling and computational challenges in comparison to the traditional approach of function specific decision-making, which justifies the continued scarcity of literature on rigorous enterprise-wide modeling.

We investigate the challenges in modeling various aspects of production and distribution in a large and complex chemical process industry, to facilitate optimal decision-making at the strategic, tactical and operational levels.

Reprinted with permission from {Misra S, Saxena D, Kapadi M, Gudi RD, Srihari R, Short-Term Planning Framework for Enterprise-wide Production and Distribution Network of a Cryogenic Air Separation Industry. Industrial & Engineering Chemistry Research 57 (49), 16841-16861, 2018}. Copyright {2018} American Chemical Society. 

Relevant Research Articles from Group:

• Maheshwari A, Misra S, Gudi RD, Subbiah S, A Short-Term Planning Framework for the Operation of Tanker-Based Water Distribution Systems in Urban Areas. Industrial & Engineering Chemistry Research 59 (20), 9575-9592, 2020. https://doi.org/10.1021/acs.iecr.0c00303. 

• Maheshwari A, Misra S, Gudi RD, Subbiah S, Laspidou C, Stochastic Optimization Model for Short-term Planning of Tanker Water Supply Systems in Urban Areas. IFAC-PapersOnLine 55 (7), 464-469, 2022. https://doi.org/10.1016/j.ifacol.2022.07.487.

• Misra S, Kapadi M, Gudi RD, Saxena D, Resource Optimization and Inventory Routing of the Packaged Liquefied Gas Supply Chain. Industrial & Engineering Chemistry Research 58 (18), 7579-7592, 2019. https://doi.org/10.1021/acs.iecr.8b05604. 

• Misra S, Kapadi M, Gudi RD, Resource Utilization & Supply Chain Optimization for Liquefied Gaseous Products. Computer Aided Chemical Engineering 44, 1579-1584, 2018. https://doi.org/10.1016/B978-0-444-64241-7.50258-5. 

• Misra S, Saxena D, Kapadi M, Gudi RD, Srihari R, Short-Term Planning Framework for Enterprise-wide Production and Distribution Network of a Cryogenic Air Separation Industry. Industrial & Engineering Chemistry Research 57 (49), 16841-16861, 2018. https://doi.org/10.1021/acs.iecr.8b05138.