A Hybrid Solution Approach for Electric Vehicle Routing Problem with Soft Time-Windows

Abstract

An electric vehicle routing problem (EVRP) with time windows is carried out using a hybrid algorithm. Through the modeling of problem, not only the energy consumptions and the charging durations of the EDVs, but also the conventional vehicle flow formulations and the soft time window constraints are taken into account. A hybrid solution method is proposed to solve EVRP. The proposed method combined genetic algorithm and simulated annealing algorithm to complement each other. In order to demonstrate the effectiveness of the proposed approach, simulations are carried out on a case study with 25 customers, 2 charging stations, a depot and 3 identical EDVs. The performance of the proposed method has been compared with the standalone genetic algorithm. It is resulted that the hybrid algorithm outperforms the genetic algorithm in terms of both solution accuracy and computational time.

Calculation Of The Optimum Number Of Unmanned Air Vehicles Required For Surveillance Missions

“…* Corresponding Author A solution to the problem was sought with a combination of genetic algorithm and simulated annealing algorithms. It has been obtained that the developed algorithm gives better results than the genetic algorithm in terms of both optimum result and problem solving time [13].…”