Group for Research in Decision Analysis

G-2020-70

The joint network vehicle routing game with optional customers

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We consider logistic collaborations where multiple carriers collaborate by consolidating demands, combining delivery routes, and serving new customers. Logistic collaborations are known to provide numerous benefits such as an increase in profit as well as a reduction in emissions for all parties involved. One of the challenges associated with collaborations is the allocation of the additional profits. To this end, we model the corresponding profit allocation problem as a collaborative game. Here, the profit obtained by any subset of the collaborating carriers depends on the new customers served by the remaining carriers. Specifically, we try to determine an allocation in the core based on both the best-case profit and the worst-case profit that each subset of carriers can attain. To achieve this, we propose a heuristic row generation algorithm. We verify the performance of this algorithm on instances derived from benchmark instances of the capacitated vehicle routing problem. We show that our heuristic algorithm scales well with respect to the number of carriers considered and provides allocations similar to those obtained by enumerating all best-case and worst-case profits of each coalition.

, 27 pages