Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
Solving multiple scenarios in a combinatorial auction
Computers and Operations Research
Solving Truckload Procurement Auctions Over an Exponential Number of Bundles
Transportation Science
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Transportation Logistics Services from Cloud
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
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Combinatorial reverse auctions can be used by shippers in order to procure transportation services from carriers. After carriers have submitted their bids, a shipper has to decide about the allocation of transport services to carriers, i. e., a shipper has to solve the winner determination problem of the auction. This paper focuses on a bicriteria winner determination problem in which a shipper has to select a subset of the set of bids and simultaneously decide about the desired trade-off between total transportation costs and the quality of the entire transportation services. To solve this bicriteria optimization problem a metaheuristic is developed that computes a set of non-dominated solutions based on the concepts of multi-start, large neighborhood search and a bicriteria branch-and-bound procedure. Compared to previous results in the literature, the proposed algorithm is able to improve the set of non-dominated solutions for 14 out of 30 benchmark instances.