Sustainable-responsive winner determination for transportation service procurement auctions under accidental disruptions

2021 ◽  
pp. 128833
Author(s):  
Xiaohu Qian ◽  
Mingqiang Yin ◽  
Felix T.S. Chan ◽  
Jiahua Zhang ◽  
Min Huang
Keyword(s):  
Procurement Auctions ◽  
Winner Determination ◽  
Transportation Service ◽  
Service Procurement

A two-stage stochastic winner determination model integrating a hybrid mitigation strategy for transportation service procurement auctions

2020 ◽  
Vol 149 ◽  
pp. 106703 ◽  
Author(s):  
Xiaohu Qian ◽  
Felix T.S. Chan ◽  
Mingqiang Yin ◽  
Qingyu Zhang ◽  
Min Huang ◽  
...  
Keyword(s):  
Mitigation Strategy ◽  
Procurement Auctions ◽  
Two Stage ◽  
Winner Determination ◽  
Transportation Service ◽  
Service Procurement

A transportation service procurement problem with combinatorial auction

ICSSSM11 ◽  
2011 ◽  
Author(s):  
Tian Tian ◽  
Ning Wang ◽  
Hong Ma ◽  
Andrew Lim
Keyword(s):  
Combinatorial Auction ◽  
Transportation Service ◽  
Service Procurement

scholarly journals Combinatorial Auctions for Transportation Service Procurement: The Carrier Perspective

2003 ◽  
Vol 1833 (1) ◽  
pp. 40-46 ◽  
Author(s):  
Jiongjiong Song ◽  
Amelia Regan
Keyword(s):  
Cost Savings ◽  
Combinatorial Auctions ◽  
Transportation Services ◽  
Service Levels ◽  
Single Carrier ◽  
Sealed Bid ◽  
Transportation Service ◽  
Simple Simulation ◽  
Delivery Routes ◽  
Service Procurement

The procurement of transportation services is an important task for shippers because of the need to control costs while providing high service levels. When shippers need to transport goods and materials, they seek transportation services from outside companies and typically issue a request for quotes from a group of carriers. The shippers then assign contracts on the basis of negotiated service charges. This process is similar to a simple sealed-bid auction in which each bidder submits a sealed bid for a single item. In the past, when shippers needed to procure transportation services for a set of distinctive delivery routes (called lanes), they would obtain quotes for each lane individually and repeat the simple auction process for each lane. Alternatively, they might negotiate for bundles of lanes with a single carrier at a time. However, in the last several years, software has been developed to enable shippers to make all lanes available for bidding simultaneously and to enable carriers to simultaneously bid on combinations of individual lanes. This method of awarding contracts, conventionally called a combinatorial auction, has resulted in significant cost savings for shippers. This research examines the benefits of combinatorial auctions primarily from the carrier's perspective. On the basis of a simple simulation model, preliminary findings suggest that carrier benefits can also be significant.

Combinatorial Bid Generation Problem for Transportation Service Procurement

2005 ◽  
Vol 1923 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Xiubin Wang ◽  
Mu Xia
Keyword(s):  
Service Providers ◽  
Optimality Criterion ◽  
Combinatorial Auctions ◽  
Combinatorial Auction ◽  
Routing Problem ◽  
Transportation Service ◽  
Insertion Method ◽  
Truck Routing ◽  
Service Procurement ◽  
Generation Problem

In combinatorial auctions, solving the bid generation problem (BGP) for bidders is critical to achieving efficiency. However, in the recent surge of combinatorial auction research, little attention has been paid to the BGP. In this paper, the BGP faced by transportation service providers is studied. First, the bidder's optimality criterion of a combinatorial bid is clarified, and then the focus is on the bundling method when an OR bid language is used. Through examples, bundles generated by solving the optimal truck routing problem were examined, and it was found that the resulting bid might not be optimal. This heuristic is compared with a simple nearest insertion method. The simulation result shows that whereas the former outperforms the latter in most cases, many times the latter outperforms the former by 5% to 8%.

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