Apple cold-chain logistics path optimization system considering vibration loss and method thereof

Abstract

The invention provides an Apple cold-chain logistics path optimization system and method considering vibration loss, and the method comprises the following steps: collecting data required by cold-chain logistics distribution, including client point information, real-time road condition information, vehicle vibration acceleration and vehicle driving information; establishing an apple vibration loss calculation model in the transportation process according to the characteristics of the apples; according to the vehicle transportation cost, the goods damage cost, the refrigeration cost, the time window constraint violation cost and the carbon emission cost, an Apple cold-chain logistics distribution path optimization model with the minimum total cost as the target is established; solving the apple cold-chain logistics distribution path optimization model by using an improved ant colony algorithm; according to the detected CO2 concentration, temperature and vibration loss, the method is used for monitoring the apple quality condition in real time, establishing a feedback adjustment mechanism, and giving loss reduction measures according to the apple quality condition. The optimal distribution path is selected in combination with an algorithm, and cost reduction and benefit increase of apple cold-chain logistics transportation are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of cold chain logistics path optimization, and in particular to an apple cold chain logistics path optimization system and method taking vibration loss into consideration. Background Art

[0002] In recent years, with the rapid development of my country's economy, the living standards and consumption capacity of urban and rural residents have continued to improve, people's food consumption concepts have gradually changed from single to diversified, the demand for fresh fruits has increased day by day, and the cold chain logistics industry has a good development momentum. However, with the continuous increase in demand for cold chain logistics, the cargo damage rate of transported products has gradually increased, especially the post-production loss of agricultural products and the waste of food circulation. The problem of unbalanced and insufficient development of cold chain logistics has become increasingly prominent. The increasing market demand for fresh products has brought opportunities to the cold chain logistics industry, but also put forward higher requirements for cold chain logistics distribution.

[0003] Cold chain logistics refers to a systematic project that keeps the products in a temperature environment required to maintain their quality throughout the entire process of production, storage, transportation, processing and sales based on the characteristics of refrigerated and frozen products, so as to reduce the loss of products. Due to the characteristics of high energy consumption and high carbon emissions, how to optimize the distribution route, improve transportation efficiency, reduce energy consumption, and ensure that products reach consumers quickly in the best condition has become a research hotspot in cold chain logistics.

[0004] In the current research on cold chain logistics route optimization, for products that are susceptible to collisions, when considering the cost of cargo loss, it is usually overlooked that the vibration generated during transportation will also cause damage to the goods. Especially in the logistics and distribution process of fresh fruits, the fruits are often affected by the vibration of the transportation vehicles. The severe vibration will cause the fruits to squeeze and collide with each other, increase the loss of the fruits themselves, and thus seriously reduce the quality of the fruits. Summary of the invention

[0005] In view of the shortcomings in the prior art, the present invention provides an apple cold chain logistics path optimization system and method taking vibration loss into consideration. By analyzing the characteristics of apples themselves, a vibration loss prediction model is established to monitor the vibration damage of apples during transportation, and vibration loss is incorporated into the cost analysis. An optimization model is established by comprehensively considering factors such as carbon emissions and time window constraints. The best distribution path is selected in combination with an algorithm to achieve cost reduction and efficiency improvement in apple cold chain logistics transportation.

[0006] The present invention achieves the above technical objectives through the following technical means.

[0007] A method for optimizing the path of cold chain logistics of apples considering vibration loss comprises the following steps:

[0008] Collect data required for cold chain logistics distribution, including customer point information, real-time road condition information, vehicle vibration acceleration and vehicle driving information;

[0009] According to the characteristics of apples, a calculation model for vibration loss of apples during transportation was established;

[0010] According to the vehicle transportation cost, cargo damage cost, refrigeration cost, time window constraint violation cost and carbon emission cost, an apple cold chain logistics distribution path optimization model with the goal of minimizing the total cost is established;

[0011] The improved ant colony algorithm is used to solve the apple cold chain logistics distribution path optimization model;

[0012] The detected CO2 concentration, temperature and vibration loss are used to monitor the quality of apples in real time, establish a feedback adjustment mechanism, and provide loss reduction measures based on the quality of apples.

[0013] Furthermore, the calculation model of the vibration loss of apples during the transportation process is as follows:

[0014]

[0015] Among them, L is the vibration loss of a single vehicle; q is the transportation volume of a single vehicle; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0;

[0016] Furthermore, the apple cold chain logistics distribution path optimization model is:

[0017]

[0018] Among them, TC is the vehicle transportation cost, FC is the cargo damage cost, P(R) is the refrigeration cost, P(t i ) is the penalty cost for violating the time window constraint, and P(C) is the carbon emission cost.

[0019] Further, the vehicle transportation cost is expressed as:

[0020]

[0021] Where: k represents the vehicle number (k = 1, 2, 3, ..., m), m is the total number of vehicles in the Apple distribution center; sign (x k ) indicates whether vehicle k participates in the distribution; A is the fixed cost of each vehicle; i and j represent different customers, and n is the total number of customers; when i=0 or j=0, i or j represents the distribution center; indicates that vehicle k travels from customer i to customer j; when i = 0, It is represented as vehicle k driving from the distribution center to customer j; when j = 0, It is represented as vehicle k driving from customer i to the distribution center; when vehicle k drives from customer i to customer j, then When vehicle k does not travel from customer i to customer j, then d ij represents the Euclidean distance between customer i and customer j; B is the unit fuel consumption cost;

[0022] The cost of cargo damage is:

[0023]

[0024] Where: P1 is the unit value of fresh apples; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0; θ1 is the spoilage rate of the product during transportation; θ2 is the spoilage rate during unloading (θ1<θ2); q i represents the demand of customer i; represents the time when delivery vehicle k arrives at customer i; represents the time when delivery vehicle k leaves the distribution center, t si represents the service time required by customer i; Indicates whether the delivery task of customer i is completed by vehicle k. When the delivery task of customer i is completed by vehicle k, then If the delivery task of customer i by vehicle k is not completed, then is the weight of apples left when vehicle k leaves customer i;

[0025] The cooling cost is:

[0026]

[0027] Where: P(R)1 is the cost of turning on the refrigeration device of the vehicle during the transportation stage; P(R)2 is the cost of turning on the refrigeration device of the vehicle during the unloading stage; P2 is the refrigeration cost per unit time during the transportation process; t ij represents the transportation time from customer i to customer j; P2' is the refrigeration cost per unit time during the unloading process; represents the service time of delivery vehicle k at customer i;

[0028] The cost of violating the time window constraint is:

[0029]

[0030] The time window refers to the time period [e i ,l i ], the earliest delivery time accepted by the customer e i and the latest delivery timei Composition: α1 is the penalty coefficient for vehicles arriving earlier than the time window; α2 is the penalty coefficient for vehicles arriving later than the time window;

[0031] The cost of carbon emissions is:

[0032]

[0033] Among them, P(C) is the carbon emission cost of the entire delivery process; P3 is the unit carbon emission cost; ω is the carbon emission generated by the vehicle delivering unit goods per unit distance; μ is the carbon emission generated by the refrigeration device per unit time; is the weight of the product delivered by vehicle k from customer point i to customer point j.

[0034] Furthermore, the improved ant colony algorithm is used to solve the apple cold chain logistics distribution path optimization model, specifically:

[0035] Initialization parameters: set the number of iterations iter = 0, set the number of ants M, the maximum number of iterations maxiter, the pheromone volatility coefficient ρ, the pheromone importance factor α and the heuristic function importance factor β;

[0036] Place ants and build a taboo table to store customer points that have been visited to prevent ants from choosing them again;

[0037] Constructing a path: Determine the customer that the ant will serve next from all the unvisited customers that meet the capacity constraint and time window constraint according to the probability calculated by the state probability transition formula; the state transition formula is as follows:

[0038]

[0039] Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; η ij is the heuristic factor, usually taken as the inverse of the distance between customer i and customer j, that is, η ij =1 / d ij ; α and β are the pheromone importance and heuristic factor importance parameters respectively; Z i (t) is the normalization factor starting from customer i at time t, ensuring that the sum of the transition probabilities from customer i to all feasible customers is 1; S f The set of clients accessible to ant f.

[0040] After completing the delivery to all customer points, the path length experienced by each ant and the delivery cost of the path are calculated, including the vehicle transportation cost TC, the cargo damage cost FC, the cooling cost P(R), the penalty cost for violating the time window constraint P(t i) and carbon emission cost P(C), determine the path with the lowest total cost as the optimal path for the current iteration;

[0041] Compare the optimal paths of the current iteration obtained in each iteration, and determine the path with the smallest MinZ as the optimal path;

[0042] Global pheromone update: update pheromones and modify the taboo table according to the path currently selected by the ant. The pheromone update formula is as follows:

[0043]

[0044] Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; ρ is the pheromone volatility coefficient; is the increment of pheromone concentration from customer i to customer j; Q is the pheromone intensity; L f is the length of the route of the fth ant, L mean is the average value of this iteration path; L best is the global optimal path length; is the first weight coefficient, is the second weight coefficient;

[0045] Determine whether the maximum number of iterations has been reached. If so, output the current value as the optimal delivery path.

[0046] Furthermore, a feedback adjustment mechanism was established to provide loss reduction measures based on the quality of apples, specifically:

[0047] A threshold value of CO2 concentration, temperature or vibration loss is set. When one of the CO2 concentration, temperature or vibration loss exceeds the corresponding threshold value, the quality of the apples is not fresh. The feedback adjustment mechanism warns the driver and prompts the driver to adjust the driving speed and / or refrigeration temperature.

[0048] An optimization system for an apple cold chain logistics path optimization method considering vibration loss, comprising a data acquisition module, a vibration monitoring module, a path optimization module and a feedback adjustment module;

[0049] The data acquisition module is used to collect real-time road condition data, time window data, vehicle energy consumption data and carbon emission data;

[0050] The vibration monitoring module is used to monitor and calculate the vibration loss during transportation;

[0051] The route optimization module determines various costs in the cold chain logistics transportation process and finds the optimal delivery route through an improved ant colony algorithm;

[0052] The feedback adjustment module is used to monitor the quality status of apples in real time and provide loss reduction measures based on the quality status of apples.

[0053] The beneficial effects of the present invention are:

[0054] 1. The apple cold chain logistics route optimization system and method taking vibration loss into consideration described in the present invention establish a vibration loss prediction model by analyzing the characteristics of apples themselves, monitor the vibration damage of apples during transportation, incorporate vibration loss into cost analysis, establish an optimization model by comprehensively considering factors such as carbon emissions and time window constraints, and select the best distribution route in combination with an algorithm, thereby reducing costs and increasing efficiency in apple cold chain logistics transportation.

[0055] 2. The apple cold chain logistics route optimization system and method taking vibration loss into consideration described in the present invention can effectively deal with the excessive CO2 concentration, temperature or vibration loss during transportation through the feedback adjustment mechanism. When a parameter is detected to exceed the preset threshold, the system will promptly issue an alert to the driver to prompt him to take corresponding loss reduction measures to ensure that the apples are always in a suitable transportation environment. In addition, the feedback adjustment mechanism also has the function of responding quickly to emergencies during transportation, thereby achieving dynamic adjustment of route optimization and improving the overall efficiency of logistics distribution and the quality of fresh products. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. The drawings described below are some embodiments of the present invention. For ordinary technicians in this field, it is obvious that other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 This is a schematic diagram of the apple cold chain logistics path optimization system taking vibration losses into consideration as described in the present invention.

[0058] Figure 2 This is a flow chart of the method for optimizing the cold chain logistics path of apples taking vibration losses into consideration according to the present invention.

[0059] Figure 3 This is a flow chart of the improved ant colony algorithm described in the present invention. DETAILED DESCRIPTION

[0060] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0061] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "axial", "radial", "vertical", "horizontal", "inner", "outer" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0062] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] like Figure 2 As shown, the apple cold chain logistics path optimization method considering vibration loss of the present invention comprises the following steps:

[0064] S01: Collect data required for cold chain logistics distribution, including customer point information, real-time traffic information, vehicle Vibration acceleration and vehicle driving information, where customer point information includes customer demand and service time.

[0065] S02: According to the characteristics of apples, a vibration loss calculation model for apples during transportation is established to construct a vibration monitoring module. That is, the vibration monitoring module mainly includes an apple vibration loss calculation model, in which:

[0066] The calculation model of the vibration loss of apples during transportation is as follows:

[0067]

[0068] Among them, L is the vibration loss of a single vehicle; q is the transportation volume of a single vehicle; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0;

[0069] S03: Comprehensively consider vehicle transportation costs, cargo damage costs, refrigeration costs, time window constraint violation costs and carbon emission costs, and establish an apple cold chain logistics distribution path optimization model with the goal of minimizing total cost;

[0070] The vehicle transportation cost is expressed as:

[0071]

[0072] Where: k represents the vehicle number (k = 1, 2, 3, ..., m), m is the total number of vehicles in the Apple distribution center; sign (x k ) indicates whether vehicle k participates in the distribution; A is the fixed cost of each vehicle; i and j represent different customers, and n is the total number of customers; when i=0 or j=0, i or j represents the distribution center; indicates that vehicle k travels from customer i to customer j; when i = 0, It is represented as vehicle k driving from the distribution center to customer j; when j = 0, It is represented as vehicle k driving from customer i to the distribution center; when vehicle k drives from customer i to customer j, then When vehicle k does not travel from customer i to customer j, then d ij represents the Euclidean distance between customer i and customer j; B is the unit fuel consumption cost.

[0073] The cost of cargo damage is:

[0074]

[0075] Among them: the cargo damage cost FC is composed of the vibration loss L1 caused by transportation and the natural loss L2 during transportation and unloading. P1 is the unit value of fresh apples; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0; θ1 is the spoilage rate of the product during transportation; θ2 is the spoilage rate during unloading (θ1<θ2); q i represents the demand of customer i; represents the time when delivery vehicle k arrives at customer i; represents the time when delivery vehicle k leaves the distribution center, t si represents the service time required by customer i; Indicates whether the delivery task of customer i is completed by vehicle k. When the delivery task of customer i is completed by vehicle k, then If the delivery task of customer i by vehicle k is not completed, then is the weight of apples left when vehicle k leaves customer i.

[0076] The cooling cost is:

[0077]

[0078] Where: P(R)1 is the cost of turning on the refrigeration device of the vehicle during the transportation stage; P(R)2 is the cost of turning on the refrigeration device of the vehicle during the unloading stage; P2 is the refrigeration cost per unit time during the transportation process; t ij represents the transportation time from customer i to customer j; P2' is the refrigeration cost per unit time during the unloading process; represents the service time of delivery vehicle k at customer i;

[0079] The cost of violating the time window constraint is:

[0080]

[0081] The time window refers to the time period [e i ,l i ], which is the earliest delivery time accepted by the customer i and the latest delivery time i α1 is the penalty coefficient for vehicles arriving earlier than the time window; α2 is the penalty coefficient for vehicles arriving later than the time window.

[0082] The cost of carbon emissions is:

[0083]

[0084] Among them, P(C) is the carbon emission cost of the entire delivery process; P3 is the unit carbon emission cost; ω is the carbon emission generated by the vehicle delivering unit goods per unit distance; μ is the carbon emission generated by the refrigeration device per unit time; is the weight of the product delivered by vehicle k from customer point i to customer point j.

[0085] The apple cold chain logistics distribution path optimization model is:

[0086]

[0087] Among them, TC is the vehicle transportation cost, FC is the cargo damage cost, P(R) is the refrigeration cost, P(t i ) is the penalty cost for violating the time window constraint, and P(C) is the carbon emission cost.

[0088] S04: Use the improved ant colony algorithm to solve the apple cold chain logistics distribution path optimization model and build a path optimization module;

[0089] like Figure 3 As shown, the improved ant colony algorithm includes the following steps:

[0090] S4.1: Initialize parameters, set the number of iterations iter = 0, set the number of ants M, the maximum number of iterations maxiter, the pheromone volatility coefficient ρ, the pheromone importance factor α and the heuristic function importance factor β.

[0091] S4.2: Place ants and build a taboo table to store customer points that have been visited to prevent ants from selecting them again.

[0092] S4.3: Construct a path, and determine the customer that the ant will serve next from all the unvisited customers that meet the capacity constraint and time window constraint according to the probability calculated by the state probability transfer formula. The state transfer formula is as follows:

[0093]

[0094] Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; η ij is the heuristic factor, usually taken as the inverse of the distance between customer i and customer j, that is, η ij =1 / d ij ; α and β are the pheromone importance and heuristic factor importance parameters respectively; Z i (t) is the normalization factor starting from customer i at time t, ensuring that the sum of the transition probabilities from customer i to all feasible customers is 1; S f The set of clients accessible to ant f.

[0095] S4.4: After completing the delivery to all customer points, calculate the path length experienced by each ant and the delivery cost of the path, including vehicle transportation cost TC, cargo damage cost FC, cooling cost P(R), penalty cost for violating the time window constraint P(t i ) and carbon emission cost P(C), determine the path with the lowest total cost as the optimal path for the current iteration;

[0096] S4.5: Compare the optimal paths of the current iteration obtained in each iteration, and determine the path with the smallest MinZ as the optimal path.

[0097] S4.6: Global pheromone update: update the pheromone according to the path currently selected by the ant and modify the taboo table. The pheromone update formula is as follows:

[0098]

[0099] Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; ρ is the pheromone volatility coefficient; is the increment of pheromone concentration from customer i to customer j; Q is the pheromone intensity; L fis the length of the route of the fth ant, L mean is the average value of this iteration path; L best is the global optimal path length; is the first weight coefficient, is the second weight coefficient.

[0100] S4.7: Determine whether the maximum number of iterations has been reached. If not, go to S2, otherwise output the current value as the optimal delivery path.

[0101] S05: A feedback adjustment mechanism is established based on CO2 concentration, temperature and vibration loss. When the CO2 concentration, temperature or vibration loss exceeds the threshold, the feedback adjustment mechanism can warn the driver and suggest that he take appropriate loss reduction measures, such as adjusting the driving speed and refrigeration temperature, to ensure that the apples are always in a suitable transportation environment.

[0102] The relationship between CO2 concentration, temperature and vibration loss and the freshness of apples in the embodiment is shown in Table 1. The thresholds of CO2 concentration, temperature and vibration loss are set to 800ppm, 5°C and 10%, respectively. When a parameter exceeds the threshold, the system can warn the driver and suggest that he take appropriate loss reduction measures, such as adjusting the driving speed and / or refrigeration temperature, to ensure that the apples are always in a suitable transportation environment.

[0103] Table 1 Relationship between CO2 concentration, temperature, vibration loss and apple freshness

[0104] <![CDATA[CO2 concentration (ppm)]]> Temperature(℃) Vibration loss Freshness <600 -1～1 0～5％ Very fresh 600～800 1～5 5～10％ Generally fresh >800 >5 10～20％ Not fresh

[0105] like Figure 1 As shown, the apple cold chain logistics path optimization system considering vibration loss described in the present invention includes a data acquisition module, a vibration monitoring module, a path optimization module and a feedback adjustment module.

[0106] The data acquisition module is used to collect real-time road condition data, time window data, vehicle energy consumption data and carbon emission data.

[0107] The vibration monitoring module is used to monitor and calculate the vibration loss during transportation, specifically by using a vibration acceleration sensor to capture vibration data of different areas and obtaining the vibration loss through a calculation model.

[0108] The route optimization module determines the various costs in the cold chain logistics transportation process and finds the optimal distribution route through the improved ant colony algorithm. The feedback adjustment module monitors the quality of apples in real time, responds quickly to emergencies, and dynamically adjusts the route optimization strategy. When vibration loss or temperature exceeds the threshold, it can warn the driver and suggest adjusting the driving speed or refrigeration temperature to ensure that the apples are always in a suitable transportation environment.

[0109] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0110] The series of detailed descriptions listed above are only specific descriptions of feasible embodiments of the present invention. They are not intended to limit the scope of protection of the present invention. All equivalent embodiments or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for optimizing the cold chain logistics path of apples considering vibration loss, characterized in that: The steps include: Collect data required for cold chain logistics distribution, including customer point information, real-time road condition information, vehicle vibration acceleration and vehicle driving information; According to the characteristics of apples, a calculation model for vibration loss of apples during transportation was established; According to the vehicle transportation cost, cargo damage cost, refrigeration cost, time window constraint violation cost and carbon emission cost, an apple cold chain logistics distribution path optimization model with the goal of minimizing the total cost is established; The improved ant colony algorithm is used to solve the apple cold chain logistics distribution path optimization model; The detected CO2 concentration, temperature and vibration loss are used to monitor the quality of apples in real time, establish a feedback adjustment mechanism, and provide loss reduction measures based on the quality of apples.

2. The method for optimizing the cold chain logistics path of apples considering vibration loss according to claim 1, characterized in that: The calculation model of the vibration loss of apples during transportation is as follows: Among them, L is the vibration loss of a single vehicle; q is the transportation volume of a single vehicle; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0.

3. The method for optimizing the cold chain logistics path of apples considering vibration loss according to claim 1, characterized in that: The apple cold chain logistics distribution path optimization model is: Among them, TC is the vehicle transportation cost, FC is the cargo damage cost, P(R) is the refrigeration cost, P(t i ) is the penalty cost for violating the time window constraint, and P(C) is the carbon emission cost.

4. The method for optimizing the cold chain logistics path of apples considering vibration loss according to claim 3 is characterized in that: The vehicle transportation cost is expressed as: Where: k represents the vehicle number (k = 1, 2, 3, ..., m), m is the total number of vehicles in the Apple distribution center; sign (x k ) indicates whether vehicle k participates in the distribution; A is the fixed cost of each vehicle; i and j represent different customers, and n is the total number of customers; when i=0 or j=0, i or j represents the distribution center; indicates that vehicle k travels from customer i to customer j; when i = 0, It is represented as vehicle k driving from the distribution center to customer j; when j = 0, It is represented as vehicle k driving from customer i to the distribution center; when vehicle k drives from customer i to customer j, then When vehicle k does not travel from customer i to customer j, then d ij represents the Euclidean distance between customer i and customer j; B is the unit fuel consumption cost; The cost of cargo damage is: Where: P1 is the unit value of fresh apples; σ is the vibration damage time sensitivity factor; G0 is the vehicle vibration acceleration; is a constant coefficient greater than 0; θ1 is the spoilage rate of the product during transportation; θ2 is the spoilage rate during unloading (θ1<θ2); q i represents the demand of customer i; represents the time when delivery vehicle k arrives at customer i; represents the time when delivery vehicle k leaves the distribution center, t si represents the service time required by customer i; Indicates whether the delivery task of customer i is completed by vehicle k. When the delivery task of customer i is completed by vehicle k, then If the delivery task of customer i by vehicle k is not completed, then is the weight of apples left when vehicle k leaves customer i; The cooling cost is: Where: P(R)1 is the cost of turning on the refrigeration device of the vehicle during the transportation stage; P(R)2 is the cost of turning on the refrigeration device of the vehicle during the unloading stage; P2 is the refrigeration cost per unit time during the transportation process; t ij represents the transportation time from customer i to customer j; P2' is the refrigeration cost per unit time during the unloading process; represents the service time of delivery vehicle k at customer i; The cost of violating the time window constraint is: The time window refers to the time period [e i ,l i ], the earliest delivery time accepted by the customer i and the latest delivery time i Composition: α1 is the penalty coefficient for vehicles arriving earlier than the time window; α2 is the penalty coefficient for vehicles arriving later than the time window; The cost of carbon emissions is: Among them, P(C) is the carbon emission cost of the entire delivery process; P3 is the unit carbon emission cost; ω is the carbon emission generated by the vehicle delivering unit goods per unit distance; μ is the carbon emission generated by the refrigeration device per unit time; is the weight of the product delivered by vehicle k from customer point i to customer point j.

5. The method for optimizing the cold chain logistics path of apples considering vibration loss according to claim 1, characterized in that: The improved ant colony algorithm is used to solve the apple cold chain logistics distribution path optimization model, specifically: Initialization parameters: set the number of iterations iter = 0, set the number of ants M, the maximum number of iterations maxiter, the pheromone volatility coefficient ρ, the pheromone importance factor α and the heuristic function importance factor β; Place ants and build a taboo table to store customer points that have been visited to prevent ants from choosing them again; Constructing a path: Determine the customer that the ant will serve next from all the unvisited customers that meet the capacity constraint and time window constraint according to the probability calculated by the state probability transition formula; the state transition formula is as follows: Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; η ij is the heuristic factor, usually taken as the inverse of the distance between customer i and customer j, that is, η ij =1 / d ij ; α and β are the pheromone importance and heuristic factor importance parameters respectively; Z i (t) is the normalization factor starting from customer i at time t, ensuring that the sum of the transition probabilities from customer i to all feasible customers is 1; S f The set of clients accessible to ant f. After completing the delivery to all customer points, the path length experienced by each ant and the delivery cost of the path are calculated, including the vehicle transportation cost TC, the cargo damage cost FC, the cooling cost P(R), the penalty cost for violating the time window constraint P(t i ) and carbon emission cost P(C), determine the path with the lowest total cost as the optimal path for the current iteration; Compare the optimal paths of the current iteration obtained in each iteration, and determine the path with the smallest MinZ as the optimal path; Global pheromone update: update pheromones according to the path currently selected by the ant and modify the taboo table. The pheromone update formula is as follows: Among them, τ ij (t) represents the pheromone concentration from customer i to customer j at time t; ρ is the pheromone volatility coefficient; is the pheromone concentration increment from customer i to customer j; Q is the pheromone intensity; L f is the length of the route of the fth ant, L mean is the average value of this iteration path; L best is the global optimal path length; is the first weight coefficient, is the second weight coefficient; Determine whether the maximum number of iterations has been reached. If so, output the current value as the optimal delivery path.

6. The method for optimizing the apple cold chain logistics path considering vibration loss according to claim 1, characterized in that: Establish a feedback adjustment mechanism and provide loss reduction measures based on the quality of apples, specifically: A threshold value of CO2 concentration, temperature or vibration loss is set. When one of the CO2 concentration, temperature or vibration loss exceeds the corresponding threshold value, the quality of the apples is not fresh. The feedback adjustment mechanism warns the driver and prompts the driver to adjust the driving speed and / or refrigeration temperature.

7. An optimization system for the apple cold chain logistics path optimization method considering vibration loss according to any one of claims 1 to 6, characterized in that: It includes data acquisition module, vibration monitoring module, path optimization module and feedback adjustment module; The data acquisition module is used to collect real-time road condition data, time window data, vehicle energy consumption data and carbon emission data; The vibration monitoring module is used to monitor and calculate the vibration loss during transportation; The route optimization module determines various costs in the cold chain logistics transportation process and finds the optimal delivery route through an improved ant colony algorithm; The feedback adjustment module is used to monitor the quality status of apples in real time and provide loss reduction measures based on the quality status of apples.

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