Optimal collaborative transportation service trading in B2B e-commerce logistics. Issue 18 (17th September 2017)

• Record Type: Journal Article
• Authors: Zhang, Mengdi; Pratap, Saurabh; Huang, George Q.; Zhao, Zhiheng
• Is Part Of: International journal of production research. Volume 55:Issue 18(2017)
• Page Start: 5485
• Page End: 5501
• Publication Date: 2017-09-17
• Subjects: less-than-truckload -- carrier collaboration -- E-commerce logistics -- meta-heuristic -- system design -- optimisation -- transportation planning; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2017.1322731
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : This paper investigates a less-than-truckload carrier collaboration decision-making problem in the e-commerce logistics network. E-commerce less-than-truckload carrier collaboration problem considers multiple logistics service providers (LSPs) forming a collaborative alliance in an e-commerce logistics network. They share their transportation requests and vehicle capabilities to maximise the total profit of the entire alliance, improve their vehicle utilisation and cope with fluctuations in demand. An e-commerce logistics trading system with collaborative decisions is designed. A collaborative transportation planning model is introduced to maximise the total profit without reducing the individual profit of the carriers with information sharing. A stochastic plant-pollinator algorithm is proposed for the problem and extensive computational experiments are conducted. The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm. Furthermore, the results illustrate that the higher degree of cooperation, the more benefits for carriers. Last but not least, since the increasing gasoline price leads to the decreasing margins for the small- and medium-sized LSPs. The results also show that it is critical for them to join in the alliance to survive in the competition.