Speed Limit Constraint-based Green Vehicle Routing Problem (SL-GVRP) - A New Variant of VRP

The Vehicle Routing Problem (VRP) represents a renowned and complex challenge that has been extensively studied in the disciplines of computer science and operations research due to its broad applicability in real-world scenarios. Numerous variants of the VRP have been developed to address specific constraints, reflecting its practical significance. This paper introduces a novel variant called the Speed Limit Constraint-based Green Vehicle Routing Problem (SL-GVRP). The primary objective is to determine the optimal route that minimizes travel time by accounting for both distance and maximum speed limits between city pairs. To tackle this problem, an efficient genetic algorithm-based solution is proposed, incorporating three population seeding techniques: nearest neighbour, and the recent ODV-based EV and VV methods. The study evaluates multiple perspectives, including distance-based, time-based, and speed-based approaches. Experimental tests are conducted using instances from the TSPLIB benchmark dataset, with the analysis focusing on the act of different genetic algorithm implementations for solving the SL-GVRP. Performance is evaluated using criteria like computation time, error rate, and mean error rate.