Rajagopalan Srinivasan

TL;DR: In this article, a unified framework for modeling, monitoring and management of supply chains is proposed, which integrates the various elements of the supply chain such as enterprises, their production processes, the associated business data and knowledge and represents them in a unified, intelligent and object-oriented fashion.

TL;DR: A novel soft sensor technology based on partial least squares (PLS) regression is developed and applied to a refining process for quality prediction and the performance of the resulting soft sensor is evaluated by comparison with laboratory data and analyzer measurements.

TL;DR: In this article, an agent-based framework for supply chain decision support systems (DSSs) is proposed to integrate all the decision-making processes of a refinery, to interface with other systems in place, to incorporate dynamic data from various sources and to assist different departments concurrently.

TL;DR: In this paper, the authors presented the first continuous-time mixed integer linear programming (MILP) formulation for the short-term scheduling of operations in a refinery that receives crude from very large crude carriers via a high-volume single buoy mooring pipeline.

TL;DR: In this paper, a mixed-integer nonlinear programming (MINLP) formulation and a novel, mixedinteger linear programming (MILP)-based solution approach are presented for optimizing crude oil unloading, storage, and processing operations in a multi-CDU (crude distillation unit) refinery receiving crude from multiparcel VLCCs (very large crude carriers) through a high-volume, single-buoy mooring (SBM) pipeline and/or single-parcel tankers through multiple jetties.