Research On The Routing Problem Of Simultaneous Delivery And Pickup Vehicles Considering Carbon Emissions

The rapid pace of industrialization has led to an escalation in global climate change and environmental issues.To address this challenge,reducing corporate carbon emissions has become a focal point of attention across various sectors.Therefore,when scheduling vehicles and planning routes in logistics companies,energy conservation and emission reduction should be considered as a crucial goal.By adopting a series of measures such as employing more energy-efficient and low-carbon transportation,planning shorter routes,logistics companies have the ability to significantly curtail their carbon footprint while simultaneously accomplishing sustainable development objectives.Additionally,logistics companies often undertake pickup tasks to avoid wasted resources caused by multiple round-trip transportation or empty loads when arranging vehicle deliveries.Therefore,the logistics delivery method of simultaneous delivery and pickup has been widely adopted by relevant companies.Based on the research of domestic and foreign scholars on the Vehicle Routing Problem for Simultaneous Delivery and Pickup（VRPSDP）,this paper focuses on how to plan routes to reduce carbon emissions,that is,the Vehicle Routing Problem for Simultaneous Delivery and Pickup with Carbon Emissions Considered（VRPSDPCE）,and adopts intelligent heuristic algorithms to seek solutionsThe main research contents are as follows:（1）This study focuses on the problem of Vehicle Routing with Simultaneous Delivery and Pickup while considering carbon emissions.For the VRPSDPCE problem,aiming to minimize carbon emissions,a mathematical model is constructed and a hybrid simulated annealing algorithm（HSA）is introduced to tackle the problem.which combines an improved savings algorithm（C-W）and a neighborhood search algorithm（NSA）.To generate preliminary solutions,the algorithm employs a savings approach that relies on k-means clustering.In the process of path optimization,a range of removal and insertion operators are introduced to broaden the search area of the neighborhood.An adaptive selection strategy is adopted,and the selection probabilities of each operator are gradually adjusted through a feedback mechanism to make the algorithm more inclined to select operators with better optimization effects.The update of solutions is controlled by utilizing the Metropolis criterion derived from the simulated annealing algorithm.The proposed Hybrid Search Algorithm（HSA）is tested using the Solomon dataset and compared with other known algorithms to validate its effectiveness.Furthermore,the impact of carbon emissions on distribution routes is investigated by comparing the shortest delivery distance F₁ and the minimum carbon emissions F₂ as optimization objectives.The experimental results show that the optimal path with F₂ as the objective has a slightly longer delivery distance than the optimal path with F₁ as the objective,but the total carbon emission cost is greatly reduced.This partially achieves the goal of environmental protection and energy conservation,supplying novel concepts for the advancement of the logistics sector within a low-carbon economy.（2）This study addresses the Vehicle Routing Problem for Simultaneous Delivery and Pickup with Carbon Emissions Consideration under Dynamic Demand（VRPSDPCEDD）.It analyzes the dynamic changes in delivery demand that occur after a vehicle has departed,including situations where the original order is cancelled,the original order address is changed,and new orders appear.The impact of these changes on carbon emissions is also considered.Based on this analysis,a mathematical model is established with the goal of minimizing carbon emissions,and a hybrid optimization algorithm（HOA）based on a"pre-optimization stage+dynamic optimization stage"strategy is proposed.In the pre-optimization stage,an improved simulated annealing algorithm（ISA）is used to generate initial delivery routes by combining k-means clustering and a greedy insertion method to construct an initial solution,and multiple neighborhood operators are introduced for local optimization to obtain the initial delivery plan.In the dynamic optimization stage,real-time customer information is combined with the previously generated delivery plans to use the taboo search algorithm,which includes multiple neighborhood search operators,to re-plan the path.Experiments with different-sized test cases demonstrate that the HOA algorithm can arrange paths reasonably,effectively reduce carbon emissions,and provide logistics companies with new,greener and more environmentally friendly solutions for vehicle delivery routes.