Abstract

We provide an exact optimization algorithm for the electric vehicle routing problem with multiple recharge technologies. Our branch-and-cut-and-price algorithm relies upon a path-based formulation, where each column in the master problem represents a sequence of customer visits between two recharge stations instead of a whole route. This allows for massive decomposition, and parallel implementation of the pricing phase, exploiting the large number of independent pricing sub-problems. The algorithm could solve instances with up to thirty customers, nine recharge stations, five vehicles and three technologies to proven optimality. Near-optimal heuristic solutions were obtained with a general-purpose MIP solver from the columns generated at the root node.

Highlights

  • The electric vehicle routing problem (EVRP) is a variation of the vehicle routing problem (VRP) in which the fleet is made of electric vehicles (EVs)

  • The results show that the presence of multiple technologies makes the EVRP considerably harder and that the performances of the BCP algorithm heavily depend on the structure of the instances and on their size

  • Another option is to develop models based on arc duplication, where each pair of customers is linked by several arcs, each one corresponding to a path visiting only recharge stations; this generates a multi-graph whose size must be taken under control by suitable dominance tests

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Summary

Introduction

The electric vehicle routing problem (EVRP) is a variation of the vehicle routing problem (VRP) in which the fleet is made of electric vehicles (EVs). All these papers consider the problem with single technology and sometimes with even more simplistic assumptions, as in the cases with no partial recharge allowed and with fixed recharge time In these BCP algorithms, each column corresponds to a feasible route, which is common in the VRP literature. Page 5 of 33 8 models with node duplication in which several copies of each station are included in the graph, to correctly distinguish different recharge operations of a same vehicle at a same station Another option is to develop models based on arc duplication, where each pair of customers is linked by several arcs, each one corresponding to a path visiting only recharge stations; this generates a multi-graph whose size must be taken under control by suitable dominance tests. A tailored node duplication operation could be needed for some specific station if all branching techniques described in the remainder fail to produce an integer solution, but this never occurred in our computational tests

Feasible Paths
The Master Problem
Reduced Costs
The Pricing Sub‐Problem
An Exact Pricing Algorithm
Heuristic Pricing
Incremental Variable Disaggregation
Branching Rules
Cutting Planes
Primal Heuristics
Parallelization
Datasets
Computational Results
Capacity Cuts and Lower Bounds
B C Overall
Primal Bounds
Parallel Pricing
Branch‐and‐Cut‐and‐Price
Conclusions

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