Research On Model And Algorithm Of Open Location-Routing Problem(OLRP) For Carbon Emissions Minimization

The contradiction between economic growth and energy consumption is becoming more and more serious.Improving the efficiency of logistics system is an important means to reduce energy consumption and carbon emissions in the logistics industry.As an important part of the logistics system,scientific location of the distribution center and optimization of the vehicle route are effective ways to improve the efficiency of the logistics system and realize the balance between environment and economy.At the same time,the development of new technologies such as information and communication technology also provides important technical support for the sharing and coordination of distribution resources and distribution capabilities.Dependent on third-party logistics(3LP)can not only effectively reduce the delivery idling rate and the distribution cost,and it can reduce carbon emissions and energy consumption.Aiming to reduce the carbon emissions of the logistics system,we study the carbon emissions of open location routing problem.Models that consider low-carbon goal are established and related algorithms are designed for solutions.The main work is as follows:1.Basing on anlysizing results of the carbon emission during the location and the delivery process by the third-party company,a mathematical model of open location-routing problem(OLRP)for carbon emissions minimization is established,which considers the distribution center capacity,delivery vehicles and driving speed,and a quantum evolution algorithm is proposed to solve the problem.The dynamic revolving door and local optimization are combined to achieve better solution in the proposed algorithm.The relationship between carbon emission and cost of OLRP is obtained by solving the standard test instances.The effectiveness of the algorithm is verified by comparison with other algorithms.The model and algorithm are applied to the coal enterprises.The coal field selection and optimization of coal transportation path show that the model has practical application value.2.Aiming at the influence of uncertain road network on the carbon emissions of location-routing problem,probability function and traffic factor are proposed to express the randomness and uncertainty of path uncertainty.The dynamic road is transformed into speed function,and the model of open location-routing problem in dynamic environment for carbon emissions minimization is proposed based on the speed function.A quantum evolution algorithm combined with local search algorithm is designed to solve the problem.Simulation experiments show that traffic uncertainty has different impacts on cost and carbon emissions,and its impact on carbon emissions is higher than cost.With the increase of fixed probability of traffic uncertainty,the increase of carbon emissions is related to the number of customers,and the impact of dynamic environment on carbon emissions of different scale problems is also analyzed.3.In view of the LRP problem of dynamic demand,the impact of dynamic demand on the carbon emissions of the location and vehicle routing is studied.The dynamic problem is decomposed into the pre-optimization stage and the real-time optimization stage.The model for carbon emissions minimization OLRP with dynamic demands is proposed and a four-stage hybrid quantum differential evolution algorithm is designed to solve the problem.Dynamics quantum revolving door and the greedy quantum selection method are used to update and improve the solution.The established model and algorithm are applied to solve dynamic demands instances which are randomly generated,and the effects of dynamic demands on carbon emissions and distance are analyzed.The quantum differential evolution algorithm proposed is compared with other intelligent algorithms through standard test instances.It is verified that the QDE has better search ability and can meet the requirements of real-time dynamic demands OLRP.4.Aiming at the dynamic uncertain customer demands location routing problem,fuzzy credibility theory is proposed to represent the customer's uncertain demands.The customer's demands are described as a triangular fuzzy function.The dynamic problem is broken into pre-optimization stage and real-time stage.A two-stage model of low-carbon OLRP with dynamic fuzzy demands is established.The four-stage hybrid quantum differential algorithm is proposed to solve the problem.The influence of the credibility measure on carbon emission is obtained through simulation experiments,and the optimal parameter combination is determined by the sensitivity analysis of the credibility parameters.The research focuses on the coordinated development of logistics and environment.The location,vehicle routing and carbon emission are combined to improve the the efficiency of logistics system.The results show that the dynamic environment with certain probability has a higher impact on carbon emissions than the cost,and the average carbon emission is 71.4% higher than the cost.The best solution considering carbon emission is not the shortest distance.The minimal cost of dynamic demands obtained by the shortest distance objective will increase the carbon emission,and the average increasing rate is about 2.7%.Higher credibility measure(CPI)will increase the carbon emission,but its extra cost is significantly reduced when the CPI value is greater or equal to 0.6.The research enriches the location-routing problem theory and optimization method,and provide a research reference for the rapid development of e-commerce logistics.