Research On Mixed-Fleet Order Assignment And Route Planning For Reserved Ride-Sharing Service In Multiple Scenarios

After the goal of peak carbon dioxide emissions and carbon neutrality were put forward,the pressure of energy conservation and emission reduction in the transportation industry is increasing,and the development and use of electric vehicles has entered an accelerated stage.In this context,the coexistence of electric vehicles and gasoline vehicles will become the norm in the future.For transportation service companies,it will inevitably bring greater challenges to order assignment and route planning due to the great differences in the cruising range and energy-renewing methods of electric vehicles and gasoline vehicles.This paper studies the operation management problem of the mixed fleet of electric vehicles and gasoline vehicles.According to passenger,cargo and passenger-cargo transportation scenarios,proposed mixed integer linear models respectively,and designed the improved adaptive large neighborhood search(IALNS)algorithm.The explicit work is as follows:(1)Mixed-fleet order assignment and route planning for passengers is studied.Considering the optimal matching between multi-vehicle and multiple transportation orders,vehicle path optimization,and electric vehicle charging plans of mixed fleets,a linear mixed integer model with the objective of minimizing the operating cost and carbon emission cost is built,and the IALNS algorithm with multiple groups of damage and repair operators is constructed.The numerical experiments demonstrate the effectiveness of the proposed model and algorithm: For small-scale instances,IALNS algorithm can quickly converge to approximate global optimal solution;Compared to variable neighborhood search algorithm and large neighborhood search algorithm,IALNS algorithm can save calculation time by 8.15% and 23.81%respectively,and for large-scale instances,can reduce cost by 11.12% and15.64% respectively.Both battery capacity and carbon emission price have positive impacts on the use of electric vehicles.When the battery capacity is significantly increased,the impact of carbon emission price is reduced.These results provide decision support for the operation management and policy formulation of ride-sharing service industry.(2)Mixed-fleet order assignment and route planning for cargo is studied.Considering vehicle capacity limitations,cargo loading and unloading operation time,and electric vehicles charging,a linear mixed integer model with the objective of minimizing the operating cost and carbon emission cost is built,and numerical experiments validate the effectiveness of the model.For large-scale instances,compared to variable neighborhood search algorithm and large neighborhood search algorithm,IALNS algorithm can ave calculation time by 19.51%% and 27.06% respectively,and for large-scale instances,can reduce cost by 13.71% and 10.32% respectively.(3)Mixed-fleet order assignment and route planning for passenger-cargo is studied.The passenger-cargo service has different service subjects,which is different from traditional passenger ride-sharing services and cargo transportation services.Considering two types of order data and operational requirements,a linear mixed integer model with the objective of minimizing the operating cost and carbon emission cost is built,and numerical experiments validate the effectiveness of the model.For large-scale instances,compared to variable neighborhood search algorithm and large neighborhood search algorithm,IALNS algorithm can save calculation time by 6.84%% and33.42% respectively,and for large-scale instances,can reduce cost by 5.75%and 3.66% respectively.In the context of peak carbon dioxide emissions and carbon neutrality,how to achieve accurate order assignment and reasonable route planning,and improve the quality of passenger,cargo and passenger-cargo service,is a long-term operational management problem that has plagued transportation service companies.The models proposed in this paper are based on reality,and the research results can provide decision support for the operation management and policy formulation of the transportation service industry,and have strong practical significance for transportation service companies to cope with the current rapid development.