Business Research | 2010
Authors:
DOI: 10.1007/BF03342722
Journal: Business Research
Year: 2010
Publisher: Springer
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 10
The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper’s task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm. © 2010, The Author(s).
carrier performance; combinatorial auction; GRASP; multi-criteria decision making; Pareto optimization; set covering problem; transportation procurement