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An increase in greenhouse gases emission from the transportation sector hasled companies and the government to elevate and support the production ofelectric vehicles (EV). With recent developments in urbanization ande-commerce, transportation companies are replacing their conventional fleetwith EVs to strengthen the efforts for sustainable and environment-friendlyoperations. However, deploying a fleet of EVs asks for efficient routing andrecharging strategies to alleviate their limited range and mitigate the batterydegradation rate. In this work, a fleet of electric vehicles is considered fortransportation and logistic capabilities with limited battery capacity andscarce charging station availability. We introduce a min-max electric vehiclerouting problem (MEVRP) where the maximum distance traveled by any EV isminimized while considering charging stations for recharging. We propose anefficient branch and cut framework and a three-phase hybrid heuristic algorithmthat can efficiently solve a variety of instances. Extensive computationalresults and sensitivity analyses are performed to corroborate the efficiency ofthe proposed approach, both quantitatively and qualitatively.

Efficient algorithms for electric vehicles' min-max routing problem