Variable Disaggregation in Network Flow Problems with Piecewise Linear Costs
Operations Research
Best routes selection in international intermodal networks
Computers and Operations Research
0-1 reformulations of the multicommodity capacitated network design problem
Discrete Applied Mathematics
Models for Evaluating and Planning City Logistics Systems
Transportation Science
A genetic algorithm for the freight consolidation problem with one-dimensional container loading
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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We develop integer programming formulations and solution methods for addressing operational issues in merge-in-transit distribution systems. The models account for various complex problem features, including the integration of inventory and transportation decisions, the dynamic and multimodal components of the application, and the nonconvex piecewise linear structure of the cost functions. To accurately model the cost functions, we introduce disaggregation techniques that allow us to derive a hierarchy of linear programming relaxations. To solve these relaxations, we propose a cutting-plane procedure that combines constraint and variable generation with rounding and branch-and-bound heuristics. We demonstrate the effectiveness of this approach on a large set of test problems with instances derived from actual data from the computer industry that contain almost 500,000 integer variables.