Text

theses

Enterprise-wide optimization (EWO) has gain lot of interest in recent years as the globalization trends of past few decades have significantly increased the scale and complexity of modern process industry and increasing economic pressures to remain competitive in global marketplace. EWO entails optimization of supply, manufacturing, and distribution activities to reduce costs and inventories through an integrated and coordinated decision-making among various functions in the industry (vendors, production facilities, and distribution). One of the major challenges in achieving EWO is mathematical tools for planning and scheduling for manufacturing facilities. Main objective of this dissertation is to develop mathematical methodologies to assist in achieving EWO goals for chemical process industry. Specially, mathematical formulation for planning and scheduling decisions and decomposition strategies will be developed in order to bridge the gap between concepts and industrial application. In this work, planning and scheduling of multisite, multiproduct batch production and distribution faculties is addressed via dual decomposition based approach, which aims to reduce computational complexity through parallel computation. In the area of continuous production facilities, lack of efficient scheduling models prevents us from developing coordinated planning and scheduling tools. To address this issue, mathematical formulations for scheduling of refinery operations is developed and novel heuristics and mathematical decomposition strategies for large scale complex mixed integer linear programming models are proposed. Throughout this dissertation, case studies will be used to demonstrate the applicability of proposed decomposition approaches.

ETD_6279

Ph.D.

Includes bibliographical references

by Nikisha K. Shah

doi:10.7282/T39C709C

ETD doctoral

The author owns the copyright to this work.