A digital-based intelligent warehousing logistics system

Abstract

This invention discloses a digitally based intelligent warehousing and logistics system, relating to the field of intelligent warehousing and logistics technology. It includes an intelligent analysis module, a data collection module, and a logistics scheduling module connected to the intelligent analysis module. This invention extracts items to be transported by prioritizing them, obtains available transport vehicles for the items based on their final location and available time, identifies conflicting transport vehicles through conflict analysis of the available transport vehicles, and finally configures transport vehicles for the items to be transported through control commands. This aims to solve the technical problems of difficulty in quickly deploying available transport vehicles within a small area when there is a short-term accumulation of items to be transported, and the neglect of advance adjustment for conflicts between transport vehicle deployments.

Description

Technical Field

[0001] This invention relates to the field of intelligent warehousing and logistics technology, and more specifically to a digitally based intelligent warehousing and logistics system. Background Technology

[0002] With the rapid development of the global economy and the booming rise of e-commerce, the logistics industry is facing unprecedented challenges and opportunities. Traditional warehousing and logistics systems are gradually revealing problems such as inefficiency, high costs, and management difficulties when dealing with increasingly complex cargo storage and retrieval needs. At the same time, consumers have increasingly higher demands for delivery speed and service quality, requiring logistics companies to have more efficient systems to meet demands such as "same-day delivery" and "next-day delivery." Therefore, it is necessary to minimize handling time during cargo delivery to improve logistics efficiency.

[0003] Currently, there are many technologies related to intelligent warehousing and logistics systems in the industry. For example, patent document CN115034721A discloses a method and system for improving the efficiency of intelligent warehousing. This system has the advantage of integrating multiple warehousing equipment and scheduling them uniformly, effectively improving the efficiency of warehousing equipment. However, careful analysis reveals that when there is an accumulation of items waiting to be moved in a short period of time, this type of intelligent warehousing and logistics system has difficulty quickly calling up available handling vehicles within a small area to move the items. It can only move items sequentially according to their storage and retrieval time. This results in items that urgently need to be processed requiring manual arrangement or queuing, increasing labor costs and reducing logistics efficiency. At the same time, this type of intelligent warehousing and logistics system neglects to avoid conflicts in calling up handling vehicles by dynamically scheduling them within a small area, increasing the uncertainty of the system and reducing its flexibility.

[0004] Therefore, it is necessary to develop a new technology to solve the above technical problems. Summary of the Invention

[0005] This invention addresses the aforementioned technical problems in existing technologies by providing a digitally based intelligent warehousing and logistics system. The system prioritizes and extracts items to be transported sequentially. It then identifies available transport vehicles based on their final location and available time. Furthermore, it performs conflict analysis on these available transport vehicles to identify conflicting vehicles. Finally, it configures transport vehicles according to control commands. This system aims to solve the technical problems of difficulty in quickly deploying available transport vehicles within a small area when there is a short-term accumulation of items to be transported, and the neglect of proactively addressing conflicts between transport vehicle deployments.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A digital-based intelligent warehousing and logistics system includes: an intelligent analysis module, and a data collection module and a logistics scheduling module connected to the intelligent analysis module; The data collection module is used to acquire target data of the items to be transported at the collection and delivery points, and to acquire the final location and usable time of the transport vehicle; wherein, the target data includes location information, collection time and delivery time; the location information includes collection point location and delivery point location; The intelligent analysis module is used to prioritize the items to be transported based on the collection time and delivery time, extract the items to be transported in sequence based on the ranking, obtain the available transport vehicles for the items to be transported based on the final location and available time of the transport vehicle, and calculate the matching factor of the available transport vehicles. The logistics scheduling module is used to perform conflict analysis on the available transport vehicles for the items to be transported to obtain conflicting transport vehicles, issue control instructions based on the conflicting transport vehicles for the items to be transported, and configure transport vehicles for the items to be transported based on the control instructions and matching factors; the conflicting transport vehicles are transport vehicles that need to be called up for different items in a short period of time.

[0007] Preferably, obtaining the target data of the items to be transported at the collection point and the drop-off point includes: Extract the location of the collection point for the items to be transported in the smart warehouse and mark the location as the collection point; extract the location of the drop-off point for the items to be transported in the smart warehouse and mark the location as the drop-off point; obtain the collection time of the items to be transported at the collection point and the drop-off time at the drop-off point from the database.

[0008] Preferably, obtaining the final location and usable time of the transport vehicle includes: A1: Sequentially obtain the working status of the transport vehicle, and determine whether the obtained working status of the transport vehicle is "working"; if yes, jump to A2; if no, jump to A3; where working status includes "working" and "stationary"; A2: The current delivery vehicle's final location is the drop point it is currently transporting, and the drop time of the items transported by the current delivery vehicle at the drop point is marked as the usable time point of the current delivery vehicle; A3: Set the current location of the transport vehicle as its final location, and mark the current time as the usable time point for the current transport vehicle.

[0009] Preferably, the prioritization of items to be delivered based on collection time and delivery time includes: The items to be transported are extracted sequentially. The historical transport time of other items between the collection point and the drop-off point corresponding to the items to be transported is obtained from the database. Feature values ​​are extracted from the historical transport time to obtain the feature transport time between the current collection point and the drop-off point. The sorting factor of each item to be transported is calculated based on the feature transport time. The items to be transported are sorted by priority from large to small based on the sorting factor to obtain the sorting table.

[0010] Preferably, the step of extracting feature values ​​from historical transport times to obtain the characteristic transport time between the current collection point and the delivery point includes: Obtain the variance of several historical transport times, and determine whether the variance is greater than the variance judgment threshold. If so, remove the historical transport time that differs the most from the mode of the historical transport times, and re-perform the variance judgment until the variance is less than the variance judgment threshold. If not, retain all historical transport times. Obtain the maximum, minimum, and average historical transport times B1, B2, and B3; based on the formula TBi=(δ1×B1+δ2×B2+B3) / 2, obtain the characteristic transport time TBi between the current collection point and the delivery point; where δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1≥δ2.

[0011] Preferably, the method for calculating the ranking factor includes: Obtain the time difference TDi between the delivery time and the current time for each item to be transported, and the time difference SCI between the collection time and the delivery time. Based on the formula PYi=α×exp(-(β1×TDi / (∑TDi / i)+β2×SCi / TBi)), obtain the sorting factor PYi for each item to be transported; where i is the number of each item to be transported; ∑ is the summation symbol, and the summation range is [1,i]; TBi is the characteristic handling time corresponding to the item to be transported with number i; α is the amplitude adjustment coefficient of the exp() function set manually, and the value range of α is (0,2]; β1 and β2 are the proportional adjustment coefficients set manually, and β1+β2=1, β1≥β2.

[0012] Preferably, the step of sequentially extracting items to be transported based on sorting includes: Extract the sorting table, and extract the corresponding items to be transported in sequence according to the order of the sorting table. Determine whether the order of the extracted items to be transported is in the first 50% of the sorting table. If yes, mark the extracted items to be transported as items to be transported. If not, do nothing.

[0013] Preferably, the step of obtaining available transport vehicles for the items to be transported based on the final location and available time of the transport vehicle, and calculating the matching factor of the available transport vehicles, includes: C1: Extract the collection time of the items to be transported, and mark the transport vehicles whose available time is before the collection time as the target transport vehicle; C2: Extract the collection point of the item to be transported, and mark the target transport vehicle whose route distance from the collection point is less than the preset distance as an available transport vehicle; where the preset distance is obtained by manual setting; C3: Determine if there are 0 available transport vehicles for the items to be transported; if yes, call a spare transport vehicle to transport the items when there are 0 available transport vehicles; otherwise, jump to C4. C4: Mark the time difference between the available time and collection time of each available transport vehicle as the standby time DTj, and mark the route distance between each available transport vehicle and the collection point as Lj. Based on the formula AZj=γ1×PDT / DTj+γ2×PL / Lj, obtain the matching factor AZj of the available transport vehicle; where j is the number of the available transport vehicle, γ1 and γ2 are both proportional adjustment coefficients greater than 0, and γ1+γ2=1.

[0014] Preferably, the conflict analysis of the available transport vehicles for the items to be transported to obtain conflict transport vehicles includes: Obtain the available transport vehicles for each item to be transported, and determine whether each available transport vehicle has been marked as an available transport vehicle by different items to be transported more than once; if so, mark the current available transport vehicle as a conflicting transport vehicle; otherwise, do nothing.

[0015] Preferably, the control command issued by the conflict-based transport vehicle to the items to be transported includes: The system sequentially extracts items to be transported and determines whether there are any available transport vehicles for the extracted items that are not marked as conflict transport vehicles. If so, it issues control instruction one to the extracted items to be transported; otherwise, it issues control instruction two to the extracted items to be transported. The control instructions include control instruction one and control instruction two.

[0016] Preferably, the configuration of the transport vehicle based on control commands and matching factors for the items to be transported includes: D1: Extract the corresponding items to be transported sequentially based on the sequence number of the sorting table, and determine whether the control instruction of the extracted items to be transported is control instruction one; if yes, select the available transport vehicle with the largest matching factor AZj among the available transport vehicles that are not marked as conflict transport vehicles corresponding to the current item to be transported, and mark it as the final transport vehicle for the current item to be transported; if no, jump to D2. D2: Combine the numbers of the conflicting transport vehicles of the extracted items to be transported into a conflict number set. Determine whether the conflicting transport vehicle in the conflict number set is marked as the final transport vehicle by other items to be transported. If yes, remove the number corresponding to the conflicting transport vehicle marked as the final transport vehicle from the conflict number set and jump to D3. If no, jump to D3. D3: Mark the conflict transport vehicle with the largest matching factor AZj among the conflict transport vehicles corresponding to each number in the conflict number set as the final transport vehicle for the current item to be transported; D4; Use the final transport vehicle for each item to be transported as the transport vehicle for the corresponding item.

[0017] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention prioritizes items to be transported by collection and deployment times, extracts items sequentially based on the ranking, and obtains available transport vehicles for the items based on the final location and available time of the transport vehicles. Conflict analysis is performed on the available transport vehicles to identify conflicting transport vehicles. Control commands are issued to the items to be transported based on the conflicting transport vehicles, and transport vehicles are configured based on the control commands and matching factors. This solves the technical problems of difficulty in quickly deploying available transport vehicles within a small area when there is a short-term accumulation of items to be transported, and the neglect of advance adjustment for conflicts between transport vehicles. This invention can quickly schedule transport based on the time sensitivity of the items to be transported, and can better cope with sudden events and peak transport volumes.

[0018] 2. This invention prioritizes items by combining the required transport time with their urgency. This allows for the priority handling of urgent tasks with shorter processing times, reducing waiting time and resource waste, and improving overall transport efficiency. Furthermore, the system dynamically adjusts the transport order based on urgency and transport time, ensuring timely delivery of critical items and preventing resource waste on less urgent tasks, further enhancing overall transport efficiency and ensuring rational resource allocation. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the operation steps of the present invention; Figure 2 This is a schematic diagram of the system modules of the present invention; Figure 3 This is a schematic diagram illustrating the operational steps of configuring a transport vehicle for the items to be transported according to the present invention. Detailed Implementation

[0020] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figures 1-2This invention provides a digitally-based intelligent warehousing and logistics system, comprising: an intelligent analysis module, and a data collection module, a logistics scheduling module, and a database connected to the intelligent analysis module; wherein, Data collection module: used to acquire target data of the items to be transported at the collection point and the drop-off point, and to obtain the final location and available time of the transport vehicle; among which, the target data includes location information, collection time and drop-off time; location information includes collection point location and drop-off point location.

[0022] Intelligent Analysis Module: This module prioritizes items to be transported based on collection and delivery times, extracts items to be transported sequentially based on the ranking, obtains available transport vehicles for items to be transported based on the final location and available time of the transport vehicle, and calculates the matching factor of available transport vehicles. The logistics scheduling module is used to perform conflict analysis on the available transport vehicles for the items to be transported to obtain conflicting transport vehicles. Based on the conflicting transport vehicles, it issues control instructions to the items to be transported and configures the transport vehicles based on the control instructions and matching factors. Conflicting transport vehicles are transport vehicles that need to be called up for different items in a short period of time.

[0023] It should be noted that the items to be transported are items waiting to be moved, and the available moving vehicles are moving vehicles that can be called upon.

[0024] The present invention acquires target data of the items to be transported at the collection point and the delivery point, including: Extract the location of the collection point for the items to be transported in the smart warehouse and mark the location as the collection point; extract the location of the drop-off point for the items to be transported in the smart warehouse and mark the location as the drop-off point; obtain the collection time of the items to be transported at the collection point and the drop-off time at the drop-off point from the database.

[0025] The present invention obtains the final location and usable time of the transport vehicle, including: A1: Sequentially obtain the working status of the transport vehicle and determine whether the obtained working status of the transport vehicle is working; if yes, jump to A2; if no, jump to A3; where working status includes working and stationary.

[0026] A2: The current delivery vehicle's final location is the drop point it is currently transporting, and the drop time of the items transported by the current delivery vehicle at the drop point is marked as the usable time point of the current delivery vehicle.

[0027] A3: Set the current location of the transport vehicle as its final location, and mark the current time as the usable time point for the current transport vehicle.

[0028] It should be noted that when obtaining the final location and usable time of the transport vehicle, this invention does not only consider idle transport vehicles, but also transport vehicles that are being transported. Taking both types of transporters into account can improve the flexibility of system planning and provide more transport options for the items to be transported.

[0029] In addition, the sequential acquisition of the operating status of the transport vehicles is based on the manually set order of their numbers.

[0030] This invention prioritizes items to be delivered based on collection and delivery times, including: The items to be transported are extracted sequentially. The historical transport time of other items between the collection point and the drop-off point corresponding to the items to be transported is obtained from the database. Feature values ​​are extracted from the historical transport time to obtain the feature transport time between the current collection point and the drop-off point. The sorting factor of each item to be transported is calculated based on the feature transport time. The items to be transported are sorted by priority from large to small based on the sorting factor to obtain the sorting table.

[0031] Specifically, feature values ​​are extracted from historical transport times to obtain the characteristic transport time between the current collection point and delivery point, including: First, obtain the variance of several historical transport times and determine whether the variance is greater than the variance judgment threshold. If so, remove the historical transport time that differs the most from the mode of the historical transport times and re-judge the variance until the variance is less than the variance judgment threshold. Then, retain the historical transport times that have not been removed. If not, retain all historical transport times.

[0032] Secondly, obtain the maximum time B1, minimum time B2, and average value B3 of the historical handling time; based on the formula TBi=(δ1×B1+δ2×B2+B3) / 2, obtain the characteristic handling time TBi between the current collection point and the delivery point; where δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1≥δ2.

[0033] It should be noted that δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1≥δ2 is because: when obtaining the characteristic transportation time between the current collection point and the delivery point through several historical transportation times, this invention sets the proportion of the maximum time B1 to be greater than the proportion of the minimum time B2. This makes the obtained characteristic transportation time tend to be a larger transportation time to a certain extent, which can improve the fault tolerance of the system in subsequent analysis and avoid the situation where the sorting factor of non-urgent items to be transported is large due to the small characteristic transportation time setting.

[0034] Specifically, the methods for calculating the ranking factor include: Obtain the time difference TDi between the delivery time and the current time for each item to be transported, and the time difference SCI between the collection time and the delivery time. Based on the formula PYi=α×exp(-(β1×TDi / (∑TDi / i)+β2×SCi / TBi)), obtain the sorting factor PYi for each item to be transported; where i is the number of each item to be transported; ∑ is the summation symbol, and the summation range is [1,i]; TBi is the characteristic handling time corresponding to the item with number i; α is the amplitude adjustment coefficient of the exp() function set manually, and the value range of α is (0,2]; β1 and β2 are the proportional adjustment coefficients set manually, and β1+β2=1, β1≥β2.

[0035] When prioritizing items to be transported, this invention takes into account both the time required for transport and the urgency of transport. This allows for the priority handling of transport tasks that are both urgent and short-duration, thereby reducing waiting time and resource waste and improving overall transport efficiency. At the same time, when resources are limited, the system can dynamically adjust the transport order based on the urgency of the items and the transport time, ensuring that critical items are delivered in a timely manner and avoiding resource waste on less urgent tasks.

[0036] It should be noted that α is used to adjust the influence of time difference TDi and time difference SCi on the ranking factor PYi; when other conditions remain unchanged, the larger α is, the larger the value of the ranking factor PYi, and the smaller α is, the smaller the value of the ranking factor PYi.

[0037] It should be noted that the dependent variable of the exp(-x) function decreases as the independent variable increases, and it is a downward trending curve.

[0038] It should be noted that β1 and β2 are manually set proportional adjustment coefficients. β1 ≥ β2 because: β1 is multiplied by the proportion of the time difference TDi between the time of delivery of the item to be transported and the current time to the corresponding average time difference, while β2 is multiplied by the proportion of the time difference SCi between the time of collection and delivery to the corresponding characteristic handling time. Since the time difference TDi between the time of delivery of the item to be transported and the current time is a variable that has a significant impact on logistics efficiency in warehousing and logistics, the proportional coefficient set for the time difference TDi in this invention is not less than the proportional coefficient for the time difference SCi.

[0039] It should be noted that the average time difference refers to the value calculated by the formula ∑TDi / i, which is the average of several time differences TDi.

[0040] For example, there are three items to be shipped: Item 1, Item 2, and Item 3.

[0041] Item to be delivered 1: Obtain the time difference between the delivery time of Item to be delivered 1 and the current time, TD1=20min, and the time difference between the collection time and the delivery time, SC1=10min.

[0042] Item 2 to be delivered: Obtain the time difference between the delivery time of Item 2 and the current time, TD2=15min, and the time difference between the collection time and the delivery time, SC2=15min.

[0043] Item to be delivered 3: Obtain the time difference between the delivery time of item to be delivered 3 and the current time, TD3=10min, and the time difference between the collection time and the delivery time, SC3=15min.

[0044] Therefore, based on the formula PY1=α×exp(-(β1×TD1 / (∑TDi / i)+β2×SC1 / TB1))=0.95×exp(-(0.8×20 / ((20+15+10) / 3)+0.2×10 / 9))=0.26, the sorting factor PY1=0.26 for item 1 to be transported is obtained; where, in this embodiment, the amplitude adjustment coefficient α is 0.95, the proportional adjustment coefficient β1 is 0.8, and the proportional adjustment coefficient β2 is 0.2; the characteristic handling time TB1=9min for item 1 to be transported with number i is 1.

[0045] Based on the formula PY2=α×exp(-(β1×TD2 / (∑TDi / i)+β2×SC2 / TB2))=0.95×exp(-(0.8×15 / ((20+15+10) / 3)+0.2×15 / 16))=0.35, the sorting factor PY1=0.35 for item 1 to be transported is obtained; where, in this embodiment, the characteristic handling time TB2=16min for item 2 to be transported is corresponding to item i.

[0046] Based on the formula PY3=α×exp(-(β1×TD3 / (∑TDi / i)+β2×SC3 / TB3))=0.95×exp(-(0.8×10 / ((20+15+10) / 3)+0.2×15 / 14))=0.45, the sorting factor PY3=0.45 for item 3 to be transported is obtained; where, in this embodiment, the characteristic handling time TB2=14min corresponds to item 3 to be transported.

[0047] This invention extracts items to be transported sequentially based on a sorting method, including: Extract the sorting table, and extract the corresponding items to be transported in sequence according to the order of the sorting table. Determine whether the order of the extracted items to be transported is in the first 50% of the sorting table. If yes, mark the extracted items to be transported as items to be transported. If not, do nothing.

[0048] In this invention, available transport vehicles for transporting items are obtained based on the final location and available time of the transport vehicle, and a matching factor for the available transport vehicles is calculated, including: C1: Extract the collection time of the items to be transported, and mark the transport vehicles whose available time is before the collection time as target transport vehicles.

[0049] C2: Extract the collection point of the item to be transported, and mark the target transport vehicle whose route distance from the collection point is less than the preset distance as an available transport vehicle; where the preset distance is obtained by manual setting.

[0050] C3: Determine if there are 0 available transport vehicles for the item to be transported; if yes, call a backup transport vehicle to transport the item when there are 0 available transport vehicles; otherwise, jump to C4. Calling a backup transport vehicle to transport the item when there are 0 available transport vehicles can be understood as: there are no transport vehicles available to transport the current item, so a backup transport vehicle is called to transport it.

[0051] C4: Mark the time difference between the available time and collection time of each available transport vehicle as the standby time DTj, and mark the route distance between each available transport vehicle and the collection point as Lj. Based on the formula AZj=γ1×PDT / DTj+γ2×PL / Lj, obtain the matching factor AZj of the available transport vehicle; where j is the number of the available transport vehicle, γ1 and γ2 are both proportional adjustment coefficients greater than 0, and γ1+γ2=1.

[0052] In this invention, conflict-prone transport vehicles are obtained by performing conflict analysis on available transport vehicles for the items to be transported, including: Obtain the available transport vehicles for each item to be transported, and determine whether each available transport vehicle has been marked as an available transport vehicle by different items to be transported more than once; if so, mark the current available transport vehicle as a conflicting transport vehicle; otherwise, do nothing.

[0053] In this invention, a control command is issued based on a conflict-handling vehicle to transport items, including: The system sequentially extracts items to be transported and determines whether there are any available transport vehicles for the extracted items that are not marked as conflict transport vehicles. If so, it issues control instruction one to the extracted items to be transported; otherwise, it issues control instruction two to the extracted items to be transported. The control instructions include control instruction one and control instruction two.

[0054] Please see Figure 3 In this invention, the transport vehicle is configured based on control commands and matching factors to transport the items, including: D1: Extract the corresponding items to be transported sequentially based on the sequence number in the sorting table, and determine whether the control instruction for the extracted items to be transported is control instruction one; if yes, select the available transport vehicle with the largest matching factor AZj among the available transport vehicles that are not marked as conflict transport vehicles corresponding to the current item to be transported, and mark it as the final transport vehicle for the current item to be transported; if no, jump to D2. It should be noted that this jump to D2 is the control instruction two mentioned above.

[0055] D2: Integrate the numbers of the conflicting transport vehicles of the extracted items to be transported into a conflict number set. Determine whether the conflicting transport vehicle corresponding to the conflict number set has been marked as the final transport vehicle by other items to be transported. If yes, remove the number corresponding to the conflicting transport vehicle marked as the final transport vehicle from the conflict number set and jump to D3. If no, jump to D3.

[0056] D3: Mark the conflict transport vehicle with the largest matching factor AZj among the conflict transport vehicles corresponding to each number in the conflict number set as the final transport vehicle for the current item to be transported.

[0057] D4; Use the final transport vehicle for each item to be transported as the transport vehicle for the corresponding item.

[0058] It should be noted that after jumping to D2 through the "If No" step in D1, the entire D2 step is under the constraint that "all the transport vehicles corresponding to the items to be transported are conflicting transport vehicles". In this case, the "If" step in D2 can be understood as, among all the conflicting transport vehicles, there is a case where it is marked as the final transport vehicle by other transport vehicles. In this case, the conflicting transport vehicles corresponding to the final transport vehicle are removed, and then the final transport vehicle is selected through step D3. The "If No" step in D2 can be understood as, there is no case where it is marked as the final transport vehicle by other transport vehicles. In this case, the final transport vehicle can be selected directly through step D3.

[0059] It is worth noting that when configuring transporters in warehousing and logistics, there may be situations where too many items to be transported in a short period of time lead to multiple calls to the same transporter, which can cause errors in the system logic. This invention addresses this by performing conflict analysis on the transporters and pre-processing potentially conflicting calls, preventing different items from calling the same transporter and improving the system's stability and adaptability.

[0060] It should be noted that determining whether the conflicting transport vehicle corresponding to the extracted item to be transported is marked as another item to be transported in the final transport vehicle by other items to be transported means: other items to be transported that are in the same sorting table as the extracted item to be transported.

[0061] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0062] The working principle of this invention is as follows: First, the location of the items to be transported at the collection and delivery points, along with the collection and delivery times, are obtained, along with the final location and available time of the transport vehicles. Then, the items to be transported are prioritized based on their collection and delivery times, and the items are extracted sequentially based on this prioritization. Available transport vehicles for each item are then identified based on their final location and available time. Finally, conflict analysis is performed on the available transport vehicles to identify conflicting transport vehicles. Control commands are then issued to the items to be transported based on these conflicting transport vehicles, and the transport vehicles are configured accordingly. This allows for rapid scheduling based on the time sensitivity of the items to be transported, better addressing unexpected events and peak transport volumes.

[0063] The above description is merely a specific embodiment of the present invention. Any feature disclosed in this specification may be replaced by other equivalent or similar features unless otherwise specified. All features or steps in the disclosed methods or processes may be combined in any way, except for mutually exclusive features and / or steps.

Claims

1. A digitally-based intelligent warehousing and logistics system, characterized in that... include: The intelligent analysis module, as well as the data collection module and logistics scheduling module connected to the intelligent analysis module; The data collection module is used to acquire target data of the items to be transported at the collection and delivery points, and to acquire the final location and usable time of the transport vehicle; wherein, the target data includes location information, collection time and delivery time; the location information includes collection point location and delivery point location; The intelligent analysis module is used to prioritize the items to be transported based on the collection time and delivery time, extract the items to be transported in sequence based on the ranking, obtain the available transport vehicles for the items to be transported based on the final location and available time of the transport vehicle, and calculate the matching factor of the available transport vehicles. The logistics scheduling module is used to perform conflict analysis on the available transport vehicles for the items to be transported to obtain conflicting transport vehicles, issue control instructions based on the conflicting transport vehicles for the items to be transported, and configure transport vehicles for the items to be transported based on the control instructions and matching factors; the conflicting transport vehicles are transport vehicles that need to be called up for different items in a short period of time.

2. The digital-based intelligent warehousing and logistics system according to claim 1, characterized in that: The acquisition of target data for the items to be delivered at collection and drop-off points includes: Extract the location of the collection point for the items to be transported in the smart warehouse and mark the location as the collection point; extract the location of the drop-off point for the items to be transported in the smart warehouse and mark the location as the drop-off point; obtain the collection time of the items to be transported at the collection point and the drop-off time at the drop-off point from the database.

3. The digital-based intelligent warehousing and logistics system according to claim 1, characterized in that: The process of obtaining the final location and usable time of the transport vehicle includes: A1: Sequentially obtain the working status of the transport vehicle, and determine whether the obtained working status of the transport vehicle is "working"; if yes, jump to A2; if no, jump to A3; where working status includes "working" and "stationary"; A2: The current delivery vehicle's final location is the drop point it is currently transporting, and the drop time of the items transported by the current delivery vehicle at the drop point is marked as the usable time point of the current delivery vehicle; A3: Set the current location of the transport vehicle as its final location, and mark the current time as the usable time point for the current transport vehicle.

4. The digital-based intelligent warehousing and logistics system according to claim 1, characterized in that: The prioritization of items to be delivered based on collection and delivery times includes: The items to be transported are extracted sequentially. The historical transport time of other items between the collection point and the drop-off point corresponding to the items to be transported is obtained from the database. Feature values ​​are extracted from the historical transport time to obtain the feature transport time between the current collection point and the drop-off point. The sorting factor of each item to be transported is calculated based on the feature transport time. The items to be transported are sorted by priority from large to small based on the sorting factor to obtain the sorting table.

5. The digital-based intelligent warehousing and logistics system according to claim 4, characterized in that: The step of extracting feature values ​​from historical transport times to obtain the characteristic transport time between the current collection point and the delivery point includes: Obtain the variance of several historical transport times, and determine whether the variance is greater than the variance judgment threshold. If so, remove the historical transport time that differs the most from the mode of the historical transport times, and re-perform the variance judgment until the variance is less than the variance judgment threshold. If not, retain all historical transport times. Obtain the maximum, minimum, and average historical transport times B1, B2, and B3; based on the formula TBi=(δ1×B1+δ2×B2+B3) / 2, obtain the characteristic transport time TBi between the current collection point and the delivery point; where δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1≥δ2.

6. The digital-based intelligent warehousing and logistics system according to claim 5, characterized in that: The method for calculating the ranking factor includes: Obtain the time difference TDi between the delivery time and the current time for each item to be transported, and the time difference SCI between the collection time and the delivery time. Based on the formula PYi=α×exp(-(β1×TDi / (∑TDi / i)+β2×SCi / TBi)), obtain the sorting factor PYi for each item to be transported; where i is the number of each item to be transported; ∑ is the summation symbol, and the summation range is [1,i]; TBi is the characteristic handling time corresponding to the item to be transported with number i; α is the amplitude adjustment coefficient of the exp() function set manually, and the value range of α is (0,2]; β1 and β2 are the proportional adjustment coefficients set manually, and β1+β2=1, β1≥β2.

7. The digital-based intelligent warehousing and logistics system according to claim 1, characterized in that: The step of sequentially extracting items to be transported based on sorting includes: Extract the sorting table, and extract the corresponding items to be transported in sequence according to the order of the sorting table. Determine whether the order of the extracted items to be transported is in the first 50% of the sorting table. If yes, mark the extracted items to be transported as items to be transported. If not, do nothing.

8. The digital-based intelligent warehousing and logistics system according to claim 1, characterized in that: The process of obtaining available transport vehicles for the items to be transported based on the final location and available time of the transport vehicle, and calculating the matching factor of the available transport vehicles, includes: C1: Extract the collection time of the items to be transported, and mark the transport vehicles whose available time is before the collection time as the target transport vehicle; C2: Extract the collection point of the item to be transported, and mark the target transport vehicle whose route distance from the collection point is less than the preset distance as an available transport vehicle; where the preset distance is obtained by manual setting; C3: Determine if there are 0 available transport vehicles for the items to be transported; if yes, call a spare transport vehicle to transport the items when there are 0 available transport vehicles; otherwise, jump to C4. C4: Mark the time difference between the available time and collection time of each available transport vehicle as the standby time DTj, and mark the route distance between each available transport vehicle and the collection point as Lj. Based on the formula AZj=γ1×PDT / DTj+γ2×PL / Lj, obtain the matching factor AZj of the available transport vehicle; where j is the number of the available transport vehicle, γ1 and γ2 are both proportional adjustment coefficients greater than 0, and γ1+γ2=1.

9. A digitally based intelligent warehousing and logistics system according to any one of claims 1-8, characterized in that: The conflict analysis of available transport vehicles for the items to be transported yields conflicting transport vehicles, including: Obtain the available transport vehicles for each item to be transported, and determine whether each available transport vehicle has been marked as an available transport vehicle by different items to be transported more than once; if so, mark the current available transport vehicle as a conflicting transport vehicle; otherwise, do nothing.

10. A digitally based intelligent warehousing and logistics system according to claim 9, characterized in that: The control instructions issued by the conflict-based transport vehicle for the items to be transported include: The system sequentially extracts items to be transported and determines whether there are any available transport vehicles for the extracted items that are not marked as conflict transport vehicles. If so, it issues control instruction one to the extracted items to be transported; otherwise, it issues control instruction two to the extracted items to be transported. The control instructions include control instruction one and control instruction two.

11. A digitally based intelligent warehousing and logistics system according to claim 10, characterized in that: The configuration of the transport vehicle based on control commands and matching factors for the items to be transported includes: D1: Extract the corresponding items to be transported sequentially based on the sequence number of the sorting table, and determine whether the control instruction of the extracted items to be transported is control instruction one; if yes, select the available transport vehicle with the largest matching factor AZj among the available transport vehicles that are not marked as conflict transport vehicles corresponding to the current item to be transported, and mark it as the final transport vehicle for the current item to be transported; if no, jump to D2. D2: Combine the numbers of the conflicting transport vehicles of the extracted items to be transported into a conflict number set. Determine whether the conflicting transport vehicle in the conflict number set is marked as the final transport vehicle by other items to be transported. If yes, remove the number corresponding to the conflicting transport vehicle marked as the final transport vehicle from the conflict number set and jump to D3. If no, jump to D3. D3: Mark the conflict transport vehicle with the largest matching factor AZj among the conflict transport vehicles corresponding to each number in the conflict number set as the final transport vehicle for the current item to be transported; D4; Use the final transport vehicle for each item to be transported as the transport vehicle for the corresponding item.

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