A lower bound for the adaptive two-echelon capacitated vehicle routing problem

Liang Song, Hao Gu and Hejiao Huang ()
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Liang Song: Harbin Institute of Technology Shenzhen Graduate School
Hao Gu: Harbin Institute of Technology Shenzhen Graduate School
Hejiao Huang: Harbin Institute of Technology Shenzhen Graduate School

Journal of Combinatorial Optimization, 2017, vol. 33, issue 4, No 1, 1145-1167

Abstract: Abstract Adaptive two-echelon capacitated vehicle routing problem (A2E-CVRP) proposed in this paper is a variant of the classical 2E-CVRP. Comparing to 2E-CVRP, A2E-CVRP has multiple depots and allows the vehicles to serve customers directly from the depots. Hence, it has more efficient solution and adapt to real-world environment. This paper gives a mathematical formulation for A2E-CVRP and derives a lower bound for it. The lower bound is used for deriving an upper bound subsequently, which is also an approximate solution of A2E-CVRP. Computational results on benchmark instances show that the A2E-CVRP outperforms the classical 2E-CVRP in the costs of routes.

Keywords: Modern logistics; Adaptive two-echelon capacitated vehicle routing problem; Lagrangian relaxation (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10878-016-0028-6

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