The electric vehicle dial-a-ride problem: Integrating ride-sharing and time-of-use electricity pricing

This paper investigates The Electric Vehicle Dial-a-Ride Problem: Integrating Ride-Sharing and Time-of-Use Electricity Pricing (DAR-RSTOU), which involves designing a set of minimum-cost routes to service all customers for a fleet of electric vehicles (EVs). The characteristics of the problem include: (1) the use of EVs and consideration of partial charging strategies; (2) a maximum ride time duration limit for each customer; (3) the possibility of ride-sharing among customers; (4) accounting for Time-of-Use (TOU) electricity pricing policies. We propose a novel mixed integer programming model to describe the problem, aiming to minimize the weighted sum of the charging, total travel, and detour penalty costs. Additionally, we have devised a customized adaptive large neighborhood search heuristic with an enhanced feasibility-checking method for rapid solution evaluation and dynamic programming to optimize the charging strategy for the fleet. Computational experiments on adapted benchmark instances from DARP literature and on instances based on real data from electric taxis in Shenzhen assess the validity of the DAR-RSTOU formulation and the heuristic algorithm. Parameter experiments highlight the algorithm's acceleration strategy effectiveness. Valuable managerial insights are derived from policy-oriented research on different electricity pricing strategies.