An Interactive Intelligent Decision Support System for Integration of Inventory, Planning, Scheduling and Revenue Management A dissertation presented to the faculty of the Russ College of Engineering and Technology of Ohio University In partial fulfillment of the requirements for the degree Doctor of Philosophy Ehsan Ardjmand August 2015 © 2015 Ehsan Ardjmand. All Rights Reserved. 2 This dissertation titled An Interactive Intelligent Decision Support System for Integration of Inventory, Planning, Scheduling and Revenue Management by EHSAN ARDJMAND has been approved for the Department of Industrial and Systems Engineering and the Russ College of Engineering and Technology by Gary R. Weckman Associate Professor of Industrial and Systems Engineering Dennis Irwin Dean, Russ College of Engineering and Technology 3 ABSTRACT ARDJMAND, EHSAN, Ph.D., August 2015, Mechanical and Systems Engineering An Interactive Intelligent Decision support system for Integration of Inventory, Planning, Scheduling and Revenue Management Director of Dissertation: Gary R. Weckman The long-term permanency and profitability of a firm requires decisions to be made wisely and on time. For this purpose, it is essential to consider all aspects of a decision in terms of its impact on revenue, planning, scheduling, and inventory in an integrated framework. In this research paper, an interactive intelligent decision support system for making an integrated decision in the presence of demand uncertainty is proposed. The system operates in a multi-product, multi-period setting, and its objective is to maximize the profit of the firm over time. To achieve its objective, the system first obtains the optimal price and capacity plan for the coming periods. The output of this first step becomes the input for the second step, in which the problem of scheduling is solved. At the end, based on the scheduling step, the optimum inventory policy is determined. To cope with demand uncertainty in the pricing and planning phase, a robust optimization model is proposed in which the demand is considered to belong to an interval and there is no knowledge (such as statistical distribution) associated with the demand. The robust problem is solved using a metaheuristic. During the scheduling step, a general setting for the problem is considered, in which each product is treated like a project with a flow network. To address the problem 4 of scheduling, a simulation optimization method is applied in which the optimization step determines the dispatch rule of the jobs and the simulation step schedules the dispatched jobs on the production line. During the inventory step, the system obtains the best schedule for ordering and storing the raw material in order to minimize the inventory cost. For this purpose, a mixed integer mathematical model is proposed and a metaheuristic is applied to obtain the best solution. All modules of the proposed decision support system are supported with a database that stores the data obtained from the shop floor and the market. This database is used to assess the costs and parameters in models by applying a cost estimation support system. To evaluate the effectiveness of the proposed decision support system, it has implemented in a small size textile production line. The data generated by the system and its users are analyzed for a period of four months. Four indicators of profit per product, overall equipment effectiveness, percentage of realized schedule and work-in-progress are monitored during these four months and their values are compared against the same time period in previous year. The results show that the system has improved in terms of profitability, equipment effectiveness and production line control. However, the work-in- progress has not improved. 5 DEDICATION To my parents and wife, Fereydoon, Tayebeh and Maria 6 ACKNOWLEDGMENTS First, I would like to express my sincere gratitude to my advisor Dr. Gary R. Weckman who helped me greatly in the course of this research. Had it not been for his confidence in me and invaluable guidance that gone far beyond this dissertation, my academic life would have not been possible. I owe him a great many thanks for his support and friendship. My deepest thanks to Dr. William A. Young for providing me the opportunity to broaden my academic perspective by teaching and involve me in various research projects. His enthusiasm, encouragement, and faith in me have been extremely contributed to this dissertation. I would also like to thank Dr. Namkyu Park for his brilliant comments and intellectual support. He was always available for my questions and knew where to look for the answers while leading me to the right direction in both theory and practice. My sincere thanks go to my dissertation committee Dr. Andy Snow and Dr. Hajrudin Pasic for their thoughtful feedback, which has added value to this research. Special thanks to Bradly Weckman for his great comments on the manuscript and Dr. Weckman’s lovely wife, Janet that always supported me spiritually. 7 TABLE OF CONTENTS Page Abstract ............................................................................................................................... 3 Dedication ........................................................................................................................... 5 Acknowledgments............................................................................................................... 6 List of Tables .................................................................................................................... 12 List of Figures ................................................................................................................... 14 1 Introduction ............................................................................................................... 18 1.1 Background ....................................................................................................... 19 1.2 Problem ............................................................................................................. 21 1.3 Significance....................................................................................................... 22 1.4 Implementation and Data Acquisition .............................................................. 22 2 Literature Review ...................................................................................................... 23 2.1 Decision Support Systems (DSS) ..................................................................... 23 2.2 Pricing and Revenue Management Systems ..................................................... 28 2.3 Forecasting Support Systems ............................................................................ 31 2.4 Cost Estimation Decision Support Systems ...................................................... 38 2.5 Planning and Scheduling Support Systems....................................................... 41 2.6 Inventory Management Systems ....................................................................... 50 2.7 Limitations ........................................................................................................ 55 3 General Framework of the System ........................................................................... 57 3.1 Cost Estimation ................................................................................................. 58 8 3.2 Pricing and Planning ......................................................................................... 58 3.3 Scheduling......................................................................................................... 59 3.4 Inventory ........................................................................................................... 59 4 Financial and Cost Estimation Module ..................................................................... 60 4.1 Inputs................................................................................................................. 60 4.1.1 Cost Centers ............................................................................................................. 60 4.1.2 Costs ......................................................................................................................... 61 4.2 Processes ........................................................................................................... 62 4.2.1 Estimating Finished Costs ........................................................................................ 62 4.2.2 Estimating Inventory Costs ...................................................................................... 63 4.2.3 Estimating Lost Sale Cost ........................................................................................ 64 4.3 Design and Outputs of Finance and Cost Estimation Module .......................... 64 5 Pricing and Planning Module .................................................................................... 66 5.1 Inputs................................................................................................................. 66 5.1.1 Inputs from Finance and Cost Estimation Module ................................................... 67 5.1.2 Resource Constraints ................................................................................................ 67 5.1.3 Demand and Uncertainty .......................................................................................... 67 5.2 Processes ..........................................................................................................