Integrated Logistics Optimization

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Integrated logistics optimization involves transportation, location and inventory management concerns. It is motivated by the high cost incurred by companies when dealing their distribution and replenishment activities. The main objective of this research program is to describe, model and develop solution techniques for a set of integrated inventory management and distribution problems. These problems arise at the three levels of decisions that a company needs to make: strategic, tactical and operational.The long-term objectives of this research program are the description, modeling and development of solution techniques for a set of integrated inventory management and distribution problems. Determining facilities location and constructing vehicle routes while minimizing inventory holding and demand satisfaction costs, will provide a realistic depiction of distribution activities taking place in global supply chains. The short-term objectives of this research proposal are (1) to design models and algorithms for the strategic facility and equipment location problems, (2) to propose tactical models and solution techniques to incorporate sustainability and environmental aspects into the combined inventory-routing problem, and (3) to model and to develop solutions for long- and short-haul transportation problems that integrate demand and inventory considerations. The common methodology used throughout this research program focuses on the development of mathematical integer programming models and efficient algorithms for complex problems arising in integrated logistics. The methods include exact algorithms that guarantee optimal solutions or provide strong lower bounds, coupled with decomposition techniques such as branch-and-cut. We will also develop powerful heuristics capable of quickly producing high-quality solutions. These include adaptive large neighborhood search, variable neighborhood search, matheuristics, rolling horizon heuristics, approximate mathematical programming algorithms, and other known and new techniques. A crucial step and significant part of the work lies in determining, for each application, how to model it, whether an exact or heuristic algorithm is appropriate, which specific approach is best, and how to implement and test it.