Large-scale operational company matching for horizontal collaboration in road transport
a commodity driven approach
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Abstract
Fierce competition force companies engaging in road transport to improve their performance. One way to increase performance in order to gain competitive advantage is by horizontal collaboration. This collaboration focusses on merging road transport of two companies. Even though it is accepted that collaboration gives opportunities for improvement by for instance sharing their fleet and make favourable combination of drops, there are still barriers to overcome. This research aims on solving the partner scarcity and selection barriers. Finding a good collaboration partner is far from easy. The developed and implemented matching model matches companies’ road transport based upon CBS shipment data. The model searches in the available companies' shipment data and determines the potential for each collaboration. The estimation algorithm is a high-speed and scalable algorithm that solves multiple depots, delivery, pickup and pickup&delivery and capacity planning problems. The results for 10 companies have shown that collaboration can save up to 20% of the total transportation costs.