Research on Vehicle Route Optimization for Half-Open Multi-Energy Urban Distribution Considering Order Priority

Abstract

Aiming at the current problems of increasingly serious tailpipe pollution of urban distribution vehicles and irrational distribution route planning, we construct a fuel-electric hybrid multi-trip multi-center half-open joint distribution vehicle routing optimization model (F-EHOMTMDVRPOPTW) considering order priority and fuzzy time window, and introduce Tent chaotic mapping combined with an improved discrete sparrow search algorithm (DSSA) with stochastic key encoding strategy for solving. Based on the traditional fuel VRP, new energy vehicles are added to form a multi-energy vehicle formation. Considering the order priority and customer time window in the context of urban distribution with non-new energy vehicle restriction, and constructing a distribution model for minimizing the total cost with the transportation cost, charging cost of new energy vehicles, carbon emission and fuel consumption cost, and penalty cost for violating the time window. On the basis of the sparrow search algorithm, Tent chaotic mapping is added and random key coding strategy is inserted for discretization, which increases the diversity of the initial population of the sparrow search algorithm and improves the algorithm’s global optimization seeking ability. Finally, the algorithms and models are analyzed in simulation experiments using benchmark test functions and arithmetic examples to verify the reasonableness of the models and the effectiveness of the algorithms, which provides theoretical basis for urban distribution and utilization of energy.