Heuristic methods for the periodic Shipper Lane Selection Problem in transportation auctions. (April 2017)

• Record Type: Journal Article
• Authors: Triki, Chefi; Mirmohammadsadeghi, Seyedmehdi; Piya, Sujan
• Is Part Of: Computers & industrial engineering. Volume 106(2017)
• Page Start: 182
• Page End: 191
• Publication Date: 2017-04
• Subjects: Shipper Lane Selection Problem -- Transportation procurement -- Auctions -- Synergy -- Simulated annealing; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.02.005
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Shipper Lane Selection Problem in transportation procurement auctions. Periodicity condition in the integer programming formulation. Heuristics based on the decomposition approach to solve large-scale problems. Extensive experimental analysis on benchmark test problems. Comparison with the state-of-the-art models and sensitivity analysis. Abstract: In the Shipper Lane Selection Problem (SLSP) a set of lanes should be classified either to be serviced by the shipper's fleet or through auction. However, it is common in real-life problems that the same lane should be served multiple times during the planning horizon. In this study, the periodicity nature of the problem is incorporated into the SLSP. Thus, a novel variant of the problem, namely the Periodic SLSP (P-SLSP) is introduced. The aim is to achieve savings on the shipper transportation costs over the extended horizon. The problem is modeled as an integer programming formulation and solved first with a general purpose software. Subsequently, three different heuristic methods have been developed to overcome the limitation of the exact full-space method. The validity of the model as well as the efficiency of the heuristics have been tested by using a properly modified set of Solomon's benchmark problems. Intensive computational analysis indicates the appropriateness of the proposed heuristics and their relevance for solving large-scale P-SLSPs.