A first multilevel cooperative algorithm for capacitated multicommodity network design
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
A survey on benders decomposition applied to fixed-charge network design problems
Computers and Operations Research
An integer programming approach to support the US Air Force's air mobility network
Computers and Operations Research
A dynamic driver management scheme for less-than-truckload carriers
Computers and Operations Research
Benders decomposition applied to multi-commodity, multi-mode distribution planning
Expert Systems with Applications: An International Journal
A Study of Demand Stochasticity in Service Network Design
Transportation Science
Models for Evaluating and Planning City Logistics Systems
Transportation Science
Computers and Operations Research
Computers and Operations Research
A hybrid approach for solving shift-selection and task-sequencing problems
CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
A metaheuristic for stochastic service network design
Journal of Heuristics
Expert Systems with Applications: An International Journal
Tabu assisted guided local search approaches for freight service network design
Information Sciences: an International Journal
A GRASP with adaptive large neighborhood search for pickup and delivery problems with transshipment
Computers and Operations Research
Logistics service network design for time-critical delivery
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Network design formulations for scheduling U.S. Air Force channel route missions
Mathematical and Computer Modelling: An International Journal
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In this paper we describe a new approach to solving the express shipment service network design problem. Conventional polyhedral methods for network design and network loading problems do not consistently solve instances of the planning problem we consider. Under a restricted version of the problem, we transform conventional formulations to a new formulation using what we termcomposite variables. By removing flow decisions as explicit decisions, this extended formulation is cast purely in terms of the design elements. We establish that its linear programming relaxation gives stronger lower bounds than conventional approaches. We apply this composite variable formulation approach to the UPS Next Day Air delivery network and demonstrate potential annual cost savings in the hundreds of millions of dollars.