I Process Industry -- Challenges in Enterprise Wide Optimization for the Process Industries -- Multi-Product Inventory Logistics Modeling in the Process Industries -- Modeling and Managing Uncertainty in Process Planning and Scheduling -- A Relative Robust Optimization Approach for Full Factorial Scenario Design of Data Uncertainty and Ambiguity -- II Supply Chain and Logistics Design -- An Enterprise Risk Management Model for Supply Chains -- Notes On Using Optimization And DSS Techniques to Support Supply Chain And Logistics Operations -- On the Quadratic Programming Approach for Hub Location Problems -- Nested Partitions and Its Applications to the Intermodal Hub Location Problem -- III Supply Chain Operation -- Event-Time Models for Supply Chain Scheduling -- A Dynamic and Data-Driven Approach to the News Vendor Problem Under Cyclical Demand -- Logic-based MultiObjective Optimization for Restoration Planning -- IV Networking and Transportation -- The Aircraft Maintenance Routing Problem -- The Stochastic Vehicle Routing Problem for Minimum Unmet Demand -- Collaboration in Cargo Transportation -- Communication Models for a Cooperative Network of Autonomous Agents.

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.