Optimization and Logistics Challenges in the Enterprise

ISBN-13: 9780387886169 / Angielski / Twarda / 2009 / 431 str.

Wanpracha Chaovalitwongse; Kevin C. Furman; Panos M. Pardalos

Opis

This book aims to bridge the gap between operations research and mathematical optimization research from the academic arena with industrial practice. The scope of much of the research in this book was suggested by contributors' industrial partners. Several topics are covered, including: - Enterprise-Wide Optimization,
- Transportation & Logistics,
- Distribution Networks,
- Operation and Process Scheduling,
- Planning & Long Term Investment,
- Simulation-Optimization,
- Optimization Under Uncertainty,
- Advances in Optimization Models and Algorithms. The book is motivated by the need to answer an emerging question from industry: "How do we go from mathematical modeling and optimization techniques to practical solutions for problems arising in the enterprise's operations?" The answer to this question will revolutionize research in optimization and logistics, as well as real business operations in the enterprise. This book makes a necessary step towards providing the answer to this question.

Spis treści

Preface.- List of Contributors.- Part I: Process Industry.- 1. Challenges in Enterprisewide Optimization for the Process Industries (Ignacio E. Grossmann, Kevin C. Furman).- 2. Multiproduct Inventory Logistics Modeling in the Process Industries (Danielle Zyngier, Jeffrey D. Kelly).- 3. Modeling and Managing Uncertainty in Process Planning and Scheduling (Marianthi Ierapetritou, Zukui Li).- 4. A Relative Robust Optimization Approach for Full Factorial Scenario Design of Data Uncertainty and Ambiguity (Tiravat Assavapokee, Matthew J. Realff, Jane C. Ammons).- Part II: Supply Chain and Logistics Design.- 5. An Enterprise Risk Management Model for Supply Chains (John M. Mulvey, Hafize G. Erkan).- 6. Notes of using Optimization and DSS Techniques to Support Supply Chain and Logistics Operations (Tan Miller).- 7. On the Quadratic Programming Approach for Hub Location Problems (Xiaoz He, Anthony Chen, Wanpracha Art Chaovalitwongse, Henry Liu).- 8. Nested Partitions and its Applications to the Intermodal Hub Location Problem (Weiwei Chen, Liang Pi, Leyuan Shi).- Part III: Supply Chain Operation.- 9. Event-Time Models for Supply Chain Scheduling (Ömer S. Benli).- 10. A Dynamic and Data-Driven Approach to the News Vendor Problem Under Cyclical Demand(Gokhan Metan, Aurélie Thiele).- 11. Logic-based Multiobjective Optimization for Restoration Planning (Jing Gong, Earl E. Lee, John E Mitchell, William A. Wallace).- Part IV: Network and Transportation 12. The Aircraft Maintenance Routing Problem (Zhe Liang, Wanpracha Art Chaovalitwongse).- 13. The Stochastic Vehicle Routing Problem for Minimum Unmet Demand (Zhihong Shen, Fernando Ordóñez, Maged M. Dessouky).- 14. Collaboration in Cargo Transportation (Richa Agarwal, Özlem Ergun, Lori Houghtalen, Okan Orsan Ozener).- 15. Communication Models for a Cooperative Network of Autonomous Agents (Ashwin Arulselvan, Clayton W. Commander, Michael J. Hirsch, Panos M. Pardalos).

Blurb

Optimization and Logistics Challenges in the Enterprise begins to answer the question of how to bridge the gap  from mathematical modeling and optimization techniques, to  practical solutions of enterprise operations. Mathematically distinct from classical supply chain management, this burgeoning research area has proven to be useful and applicable to a wide variety of industries; for example,  pharmaceutical, chemical, transportation, and shipping, to name a few.  This book consists of high quality research results and may serve as a "one-stop shop" to learn about several industrial problems and logistics challenges, and solution techniques using recent advances in computational optimization.

This work is intended for practitioners from industry who use techniques from a wide range of fields: mathematical programming, supply chain and logistics management, and process systems and operations engineering.  It will also be of value to advanced graduate and PhD students and researchers in operations research, systems engineering, and management science.