Warehouse-in and warehouse-out path planning system and method applied to stored goods

Abstract

The invention discloses a warehouse-in and warehouse-out path planning system and method applied to stored goods, and relates to the technical field of intelligent storage. The method comprises the steps of establishing a three-dimensional space structure of a warehouse, generating a menu to be stored and matching various storage schemes, carrying out importance degree assignment and priority ranking on goods, calculating the residual space and the total weight of the warehouse, judging and optimizing the space and the weight, and planning and optimizing warehouse-in and warehouse-out paths. Through the mathematical planning method, the total cost is minimized, and the space utilization rate and the access efficiency are maximized. And meanwhile, the operation condition in the warehouse is monitored in real time, the in-out path and the in-out path are dynamically adjusted, and congestion and conflicts are avoided. In addition, a high-definition camera and a sensor are further installed, and safety management in the warehouse is ensured. According to the invention, intelligent warehouse-in and warehouse-out path planning of the stored goods is realized, the warehouse management efficiency and the space utilization rate are improved, and safe storage and efficient warehouse-in and warehouse-out of the goods are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent warehousing, and in particular relates to a system and method for planning a warehouse entry and exit path for stored goods. Background Art

[0002] In warehouse management, goods in and out path planning is a crucial link. With the rapid development of the logistics industry and the booming e-commerce business, the storage demand and in and out frequency of warehouses have increased dramatically, which has put forward higher requirements for warehouse management efficiency and space utilization. Traditional in and out path planning methods often rely on manual experience and fixed rules, which are difficult to adapt to complex and changeable warehouse environments and high-intensity operation requirements. Therefore, it is particularly important to develop an efficient and intelligent in and out path planning method.

[0003] First, the complexity of the warehouse space structure poses a challenge to the inbound and outbound path planning. The interior of the warehouse is usually divided into multiple functional areas, such as shelf areas, channel areas, loading and unloading areas, etc. Each functional area has its own specific optimization requirements and restrictions. How to reasonably use these spaces to ensure the safe storage and efficient inbound and outbound of goods is a key issue that needs to be solved in the inbound and outbound path planning.

[0004] Secondly, the diversity and particularity of goods also put forward higher requirements for inbound and outbound path planning. Different goods differ in size, weight, shape, access frequency, special requirements, etc. These differences directly affect the selection of storage solutions and the planning of inbound and outbound paths. For example, fragile goods require special protection, and refrigerated goods require low-temperature storage. These special requirements must be fully considered in the planning of inbound and outbound paths.

[0005] In addition, with the development of big data and artificial intelligence technology, warehouse management is gradually transforming towards intelligence. By using historical data and real-time information, machine learning algorithms and intelligent optimization technology, accurate prediction and dynamic adjustment of the warehousing path can be achieved, thereby improving work efficiency and resource utilization. This intelligent inbound and outbound path planning method can not only adapt to the complex and changing warehousing environment, but also continuously learn and optimize to meet the needs of future warehousing management.

[0006] The present invention proposes a method for planning the in-and-out paths of stored goods. The method realizes intelligent planning and dynamic adjustment of the in-and-out paths by establishing a three-dimensional warehouse structure, generating a menu to be stored and matching multiple storage schemes, assigning importance and priority to the goods, calculating the remaining space and total weight of the warehouse, determining whether to optimize the space and weight, and planning and optimizing the in-and-out paths. The method not only improves the space utilization and operating efficiency of the warehouse, but also enhances the security and intelligence level of warehouse management. Summary of the invention

[0007] In order to overcome the shortcomings and deficiencies of the above-mentioned prior art, the first purpose of the present invention is to provide a system for planning the inbound and outbound paths of stored goods; the second purpose of the present invention is to provide a method for planning the inbound and outbound paths of stored goods.

[0008] The first object of the present invention adopts the following technical solution:

[0009] A warehouse entry and exit path planning system for warehoused goods, comprising:

[0010] Warehouse three-dimensional spatial structure establishment module: establish the warehouse's three-dimensional spatial structure according to the warehouse's shape and size parameters; divide the warehouse into multiple functional areas, including shelf areas, channel areas, and loading and unloading areas, with each functional area as an independent optimization unit;

[0011] The module for generating a menu to be stored and matching storage solutions: collects information about the goods to be put into storage, generates a menu to be stored, and assigns a unique identifier to each type of goods; matches multiple storage solutions for each type of goods, evaluates the advantages and disadvantages of each solution, and selects the best solution; storage solutions include shelf types, pallet types, stacking methods, and other storage equipment; shelf types include heavy-duty shelves, medium-duty shelves, light-duty shelves, flow shelves, and automated high-bay warehouses; pallet types include wooden pallets, plastic pallets, and metal pallets; stacking methods include single-layer stacking, multi-layer stacking, staggered stacking, and gravity stacking; other storage equipment includes rotating shelves, hanging storage, and cold storage;

[0012] Assignment and sorting module: Assign importance to each item in the storage menu. The larger the value, the more important the function of the item. Priority is assigned to the items according to the importance assigned, ensuring that important items are stored in the warehouse first and in an easily accessible location.

[0013] Spatial weight calculation module: install each item in the three-dimensional spatial structure of the warehouse, calculate the remaining space value in the warehouse and the actual weight value of the warehouse as a whole; calculate the balance coefficient and evaluate the balance state of the warehouse space and weight;

[0014] Space and weight optimization module: Determine whether space or weight optimization is needed based on the balance coefficient. If optimization is needed, adjust the distribution of goods in the warehouse to ensure the overall balance and stability of the warehouse;

[0015] Inbound and outbound path planning optimization module: collects historical data of each inbound and outbound operation, analyzes common patterns and rules; predicts future inbound and outbound demand based on historical data and real-time conditions, and performs path planning and resource allocation in advance; monitors the operation status in the warehouse in real time, dynamically adjusts the inbound and outbound paths, avoids congestion and conflicts, and improves operation efficiency;

[0016] Real-time monitoring management module: Install high-definition cameras and other sensors to monitor the operation status inside the warehouse in real time; ensure that each vehicle maintains a safe distance and plans emergency evacuation routes in advance; dynamically adjust the operation process to ensure a smooth and efficient warehousing process.

[0017] The second object of the present invention adopts the following technical solution:

[0018] A method for planning an inbound and outbound path for storage goods is used to implement an inbound and outbound path planning system for storage goods. The method flow is as follows:

[0019] Step 1: Establish the three-dimensional spatial structure of the warehouse. According to the shape and size parameters of the warehouse, use the three-dimensional modeling software to build the three-dimensional spatial structure of the warehouse and divide it into multiple functional areas, including shelf area, channel area, loading and unloading area, and each functional area is an independent optimization unit;

[0020] Step 2: Generate a menu to be stored and match multiple storage solutions, including collecting cargo information, generating a menu to be stored, matching multiple storage solutions for each cargo, and evaluating the advantages and disadvantages of each storage solution;

[0021] Step 3: Assign importance to the goods, assign values ​​to the goods according to their functional importance, and prioritize the goods according to the importance assigned, ensuring that important goods are given priority in storage and stored in easily accessible locations; record detailed information on each type of goods and the corresponding storage location, and store all goods information in the database for subsequent query and management;

[0022] Step 4: Determine whether to optimize the space. By comparing the calculated balance coefficient with the preset threshold, decide whether to optimize the warehouse space and perform partition optimization.

[0023] Step 5: Weight optimization: calculate the difference between the actual weight of the entire warehouse and the standard weight, and optimize the weight until the standard is met;

[0024] Step 6: Space optimization, calculate the difference between the remaining space in the warehouse and the standard space, and optimize the space until the standard is met;

[0025] Step 7: Inbound and outbound routes planning and optimization: collect historical data, use machine learning algorithms to analyze data, predict future inbound and outbound demand, and dynamically adjust inbound and outbound routes to avoid congestion and conflict.

[0026] Step 8: Real-time monitoring and safety management: install high-definition cameras and sensors to monitor the internal operations of the warehouse in real time to ensure safe distances and emergency evacuation route planning.

[0027] Preferably, the second step of evaluation specifically includes:

[0028] Build an optimization model and use mathematical programming methods to minimize the total cost and maximize space utilization and access efficiency. There are n storage solutions, and the evaluation indicators of each solution include storage cost, access convenience, security, space utilization, and flexibility.

[0029] The objective function is as follows: Minimize Z =ω 1 C i +ω 2 A i +ω 3 S i -ω 4 U i -ω 5 F i ;

[0030] Among them, C i is the cost of the i-th storage solution; A i is the access convenience of the i-th storage solution, expressed in time; S i is the security of the i-th storage solution, expressed as a risk score; U i is the space utilization of the i-th storage solution, expressed as a percentage; F i is the flexibility of the i-th storage solution, expressed as the adjustment ability score; ω 1 ,ω 2 ,ω 3 ,ω 4 ,ω 5 They are the evaluation indicators C i , A i , S i , U i 、F i The weight coefficient reflects the importance users attach to different evaluation indicators;

[0031] The constraints are as follows:

[0032] Space limit: The total available space V of the warehouse total Cannot exceed the actual capacity of the warehouse V max : Among them, V i is the space occupied by the i-th storage solution; x i is a binary variable (0 or 1) that selects the scheme;

[0033] Access frequency requirements: For goods that are frequently accessed, the access time A i must be less than a certain threshold T threshold : A i ≤T threshold ,

[0034] Safety requirements: For fragile or dangerous goods, the safety risk S i must be below a certain threshold S threshold :

[0035]

[0036] Special storage requirements: For goods with special storage requirements, a storage solution that meets these requirements must be selected: if the goods require refrigeration, then i∈Refrigerated storage solution.

[0037] Preferably, step 4 is as follows: Balance coefficient PH xs and the balance coefficient threshold PH min and PH max Conduct comparative analysis; if PH min <PH xs <PH max The warehouse space is not optimized; if PH xs ≤PH min or PH xs ≥PH max , then optimize the warehouse;

[0038] Taking the main stress points of the warehouse as endpoints, divide the area formed by connecting these endpoints in sequence into y equal parts. Adjust the weight and remaining space of each partition in each divided area to ensure the overall balance and stability of the warehouse.

[0039] Preferably, step five is as follows: Calculate the actual weight value Z of the entire warehouse lz Compared with the warehouse standard weight value M bz The absolute value of the difference X mz and the weight error value M wz Compare; if X mz ≤M wz , the overall weight of the warehouse is not optimized; if X mz >M wz , then weight optimization is performed; calculate the weight value M of each partition according to the formula and Among them, F mbz The standard weight value for each equally divided area; F mwz For each equally divided area, the weight error value is replaced by replacing the partially assembled goods in y equally divided areas until F mbz -M <F mwz , optimization is completed; the corresponding goods are replaced in the order of increasing importance, from heavy-weight goods to light-weight goods.

[0040] Preferably, Step Six is specifically as follows: Calculate the remaining space value K of each partition, and the remaining space value T in the warehouse jz with the standard space value T of the warehouse bz to obtain the absolute value of the difference T xz and compare it with the space error value T wz ; If T xz ≤T wz , then do not optimize the remaining space in the warehouse; If T xz >T wz , then perform space optimization;

[0041] The space optimization process is as follows: Calculate the remaining space value M of each partition. According to the formula and where F tbz is the remaining space standard value of each equal - division area; F twz is the remaining space error value of each equal - division area; Reduce the volume of the assembled goods in y equal - division areas until F tbz -K < F twz , and the optimization is completed; Reduce the corresponding assembled goods volume in the order of decreasing assembled goods volume and increasing assigned importance of the assembled goods.

[0042] Preferably, Step Seven further includes: Taking minimizing the operation efficiency as the goal, while minimizing the operation time and resource consumption. The objective function is as follows: where n is the number of objectives; ω i is the weight of the i - th objective; f i (x i ) is the cost function of the i - th objective, including path length, operation time, and resource consumption; x i is the decision variable of the i - th objective; The constraint conditions are the same as those in Step Two.

[0043] Preferably, Step Eight is specifically as follows: Install high - definition cameras and other sensors to monitor the operation situation inside the warehouse in real - time, ensure that each vehicle maintains a safe distance, and pre - plan an emergency evacuation route; When a certain transport vehicle has completed a% of the unloading, notify the next vehicle to prepare to enter the loading and unloading area.

[0044] In summary, due to the adoption of the above - mentioned technical solutions, the beneficial effects of the present invention are:

[0045] 1. The method of the present invention accurately constructs the warehouse space structure through three-dimensional modeling software, generates multiple storage plans based on the characteristics of the goods, and uses mathematical programming methods to optimize the selection. At the same time, the goods are prioritized according to their importance and access frequency, ensuring that important goods are first put into storage and stored in easy-to-access locations, thereby improving the utilization rate of storage space and reducing space waste. At the same time, by optimizing the access path of goods, the access time is shortened and the overall operating efficiency is improved. This is of great significance for improving the operational efficiency of warehouses and reducing costs.

[0046] 2. The method of the present invention introduces the concept of balance coefficient, and optimizes the warehouse by calculating the balance state between the remaining space and the total weight of the warehouse. On the basis of partition optimization, by adjusting the weight and remaining space of each partition, the overall balance and stability of the warehouse are ensured, which can avoid structural safety problems caused by uneven weight distribution in the warehouse, and improve the storage capacity and stability of the warehouse. In addition, weight and space optimization through means such as cargo replacement and volume reduction further improves the storage efficiency and flexibility of the warehouse.

[0047] 3. The method of the present invention uses machine learning algorithms to analyze historical data, identify common patterns and rules of warehousing operations, and predict future warehousing demand based on real-time conditions. At the same time, through real-time monitoring and dynamic adjustment of warehousing routes, congestion and conflict can be avoided and operational efficiency can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] 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. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A module diagram of a system for planning a path for storing and retrieving goods according to the present invention is shown;

[0050] Figure 2 A flow chart showing a method for planning a path for entering and exiting a warehouse for stored goods according to the present invention is shown;

[0051] Figure 3 The flowchart of the present invention for generating a menu to be stored and matching multiple storage schemes is shown. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In addition, the described features, structures or characteristics may be combined in one or more example embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. may be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0054] Embodiment 1:

[0055] See also Figure 1 As shown, the present embodiment is a system for planning the in-and-out path for stored goods, including a warehouse three-dimensional spatial structure establishment module, a storage menu generation and storage plan matching module, an assignment sorting module, a space weight calculation module, a space weight optimization module, an in-and-out path planning optimization module and a real-time monitoring management module.

[0056] Warehouse 3D spatial structure building module: Based on the shape and size parameters of the warehouse, use 3D modeling software to build the warehouse's 3D spatial structure; divide the warehouse into multiple functional areas, including shelf areas, channel areas, and loading and unloading areas, with each functional area as an independent optimization unit. The loading and unloading area includes the loading area and the unloading area.

[0057] Storage menu generation and storage plan matching module: collect information on goods to be put into storage, generate a storage menu, and assign a unique identifier to each type of goods; match multiple storage plans for each type of goods, evaluate the advantages and disadvantages of each plan, and select the best plan.

[0058] Assignment and sorting module: Assign importance to each product in the storage menu. The larger the value, the more important the function of the product. Priority is assigned to the products according to the importance assigned to ensure that important products are given priority in storage and stored in easily accessible locations.

[0059] Spatial weight calculation module: install each item in the three-dimensional spatial structure of the warehouse, calculate the remaining space value in the warehouse and the actual weight value of the warehouse as a whole; calculate the balance coefficient and evaluate the balance state of the warehouse space and weight.

[0060] Space and weight optimization module: Determine whether space or weight optimization is needed based on the balance coefficient. If optimization is needed, adjust the distribution of goods in the warehouse to ensure the overall balance and stability of the warehouse.

[0061] In-and-out route planning optimization module: collects historical data of each in-and-out operation, analyzes common patterns and rules; predicts future in-and-out demand based on historical data and real-time conditions, and performs route planning and resource allocation in advance; monitors the operation status in the warehouse in real time, dynamically adjusts the in-and-out routes, avoids congestion and conflicts, and improves operational efficiency.

[0062] Real-time monitoring management module: Install high-definition cameras and other sensors to monitor the operation status inside the warehouse in real time; ensure that each vehicle maintains a safe distance and plans emergency evacuation routes in advance; dynamically adjust the operation process to ensure a smooth and efficient warehousing process.

[0063] The beneficial effects of this embodiment are as follows: the system can significantly improve the efficiency of warehouse entry and exit operations, optimize space and weight distribution, and ensure the overall balance and safety of the warehouse. Real-time monitoring and safety management mechanisms effectively prevent accidents and ensure the safety of personnel and equipment. Intelligent path planning and resource allocation reduce congestion and conflicts, improve operational fluidity and response speed, and ultimately achieve efficient, safe, and intelligent warehouse management.

[0064] Embodiment 2:

[0065] See also Figure 2 As shown, a method for planning a path for entering and exiting warehouse goods in this embodiment has the following process:

[0066] Step 1: Establish the three-dimensional spatial structure of the warehouse.

[0067] According to the shape and size parameters of the warehouse, the three-dimensional spatial structure of the warehouse is established using 3D modeling software to determine the space optimization area inside the warehouse. The interior of the warehouse is divided into multiple functional areas including shelf area, channel area, loading and unloading area, and each functional area is used as an independent optimization unit.

[0068] Step 2: Generate the menu to be stored and match multiple storage solutions.

[0069] See also Figure 3 As shown, the specific process of generating the menu to be stored and matching multiple storage solutions is as follows:

[0070] S21. Collect information about the goods that are about to enter the warehouse, including the size, weight, shape, quantity, type (such as fragile goods, refrigerated goods, chemicals, etc.), access frequency, special requirements (such as temperature control, moisture-proof, shock-proof, etc.) and estimated arrival time.

[0071] S22. Generate a to-be-stored menu, list all goods that need to be put into storage, and assign a unique identifier to each type of goods.

[0072] S23. For each product in the to-be-stored menu, n different storage solutions are matched, where n is an integer greater than 1. Candidate storage solutions are generated, including shelf types, pallet types, stacking methods, and other storage devices.

[0073] Shelf types include:

[0074] Heavy-duty racks: Suitable for large and heavy goods, usually used to store palletized goods.

[0075] Medium shelves: suitable for medium-weight goods and suitable for the storage of small and medium-sized items.

[0076] Light shelves: suitable for light goods and suitable for the storage of small items.

[0077] Flow rack: Suitable for goods that are frequently in and out of the warehouse. Goods can flow in from one end and out from the other end, which facilitates first-in-first-out (FIFO) management.

[0078] Automated warehouse: suitable for large-scale, high-density storage, usually equipped with an automatic storage and retrieval system (AS / RS), suitable for the storage of large quantities of standardized goods.

[0079] Pallet types include:

[0080] Wooden pallets: suitable for heavy goods, low cost, but not water-resistant and easily damaged.

[0081] Plastic pallets: suitable for light to medium-duty goods, durable, waterproof, easy to clean, suitable for food, medicine and other industries.

[0082] Metal pallets: suitable for extra-heavy goods, strong and durable, but more expensive.

[0083] Stacking methods include:

[0084] Single-layer stacking: Suitable for fragile or irregularly shaped goods to avoid damage caused by stacking.

[0085] Multi-layer stacking: Suitable for goods of standard shapes, multi-layer stacking can improve space utilization.

[0086] Staggered stacking: suitable for long goods, which can increase stability by staggered arrangement.

[0087] Gravity stacking: suitable for flow racks, where goods slide in from one end and out from the other end, suitable for fast-turnover goods.

[0088] Other storage devices include:

[0089] Rotary storage racks: Suitable for efficient access to small items, saving space.

[0090] Suspended storage: Suitable for long or irregularly shaped goods (such as pipes, fabrics, etc.), stored by suspension, saving floor space.

[0091] Refrigerated warehouse: Suitable for goods that need to be stored at low temperatures (such as food, medicine, etc.).

[0092] S24, Storage scheme evaluation: Evaluate the advantages and disadvantages of each storage scheme, considering factors such as storage cost, access convenience, safety, etc.

[0093] S25, Build an optimization model, using mathematical programming methods (such as linear programming, integer programming, mixed integer programming, etc.) to minimize the total cost and maximize space utilization and access efficiency. There are n storage schemes, and the evaluation indicators for each scheme include storage cost, access convenience, safety, space utilization, and flexibility.

[0094] The objective function is as follows:

[0095] Minimize Z = ω 1 C i + ω 2 A i + ω 3 S i - ω 4 U i - ω 5 F i ;

[0096] Where C i is the cost of the i-th storage scheme; A i is the access convenience of the i-th storage scheme, expressed in time; S i is the safety of the i-th storage scheme, expressed as a risk score; U i is the space utilization of the i-th storage scheme, expressed as a percentage; F i is the flexibility of the i-th storage scheme, expressed as an adjustment ability score; ω 1 、ω 2 、ω 3 、ω 4 、ω 5 are the weight coefficients of the evaluation indicators C i 、A i 、S i 、U i 、F i respectively, reflecting the importance attached by users to different evaluation indicators.

[0097] The constraint conditions are as follows:

[0098] Space Limitations:

[0099] The total available space V of the warehouse total Cannot exceed the actual capacity of the warehouse V max :

[0100]

[0101] Among them, V i is the space occupied by the i-th storage solution; x i is a binary variable (0 or 1) that selects the option.

[0102] Access frequency requirements:

[0103] For goods with high frequency of storage and retrieval, the storage and retrieval time A i must be less than a certain threshold T threshold :

[0104] A i ≤T threshold ,

[0105] Security requirements:

[0106] For fragile or dangerous goods, the safety risk S i must be below a certain threshold S threshold :

[0107] S i ≤S threshold ,

[0108] Special storage requirements:

[0109] For goods with special storage requirements (such as refrigeration, moisture-proof, etc.), a storage solution that meets these requirements must be selected:

[0110] If the goods need to be refrigerated, then i∈refrigerated storage solution.

[0111] Step 3: Assign importance to the goods.

[0112] Importance assignment: Assign importance to each item in the storage menu. The larger the value, the more important the function of the item (such as high-value items, urgently needed materials, etc.).

[0113] Prioritization: Prioritize goods according to their importance to ensure that important goods are warehoused first and stored in easily accessible locations.

[0114] Record detailed information of each cargo, including volume, weight, storage plan and corresponding storage location. Store all cargo information in the database for easy subsequent query and management.

[0115] Step 6. Calculate the remaining space and total weight in the warehouse.

[0116] Remaining space calculation: Install each item in the three-dimensional space structure of the warehouse and calculate the remaining space value T in the warehouse jz And the actual weight value of the warehouse as a whole Z tz ;

[0117] Balance coefficient calculation: The balance coefficient PH is calculated through formula analysis. xs , used to evaluate the balance status of warehouse space and weight.

[0118] Step 4: Determine whether to perform space optimization.

[0119] Balance coefficient PH xs and the balance coefficient threshold PH min and PH max Conduct comparative analysis.

[0120] If PH min <PH xs <PH max The warehouse space is not optimized;

[0121] If PH xs ≤PH min or PH xs ≥PH max , then optimize the warehouse.

[0122] Partition optimization: Take the main stress points of the warehouse as endpoints (such as the four corners of the warehouse or the main supporting columns), and divide the area formed by connecting these endpoints in sequence into y equal parts (for example, y=4).

[0123] Adjust the weight and remaining space of each partition in each equally divided area to ensure the overall balance and stability of the warehouse.

[0124] Step 5: Weight optimization.

[0125] The specific methods of weight optimization are as follows:

[0126] Weight difference comparison: calculate the actual weight value Z of the warehouse as a whole lz Compared with the warehouse standard weight value M bz The absolute value of the difference X mz and the weight error value M wz Make a comparison.

[0127] If X mz ≤Mwz , the overall weight of the warehouse is not optimized;

[0128] If X mz >M wz , weight optimization is performed.

[0129] Weight optimization process: Calculate the weight value M of each partition according to the formula and Among them, F mbz The standard weight value for each equally divided area; F mwz Weight error value for each equally divided area.

[0130] Replace the partially assembled cargo in the 4 equally divided areas until F mbz -M <F mwz , optimization completed.

[0131] Cargo replacement order: Replace the corresponding assembled cargo in the order of increasing importance, from heavy-weight cargo to light-weight cargo.

[0132] Step 6: Space optimization.

[0133] Space difference comparison: Calculate the remaining space value K of each partition and the remaining space value T in the warehouse jz With warehouse standard space value T bz The absolute value of the difference T xz and spatial error value T wz for comparison.

[0134] If T xz ≤T wz , the remaining space in the warehouse will not be optimized.

[0135] If T xz >T wz , then space optimization is performed.

[0136] The space optimization process is as follows:

[0137] Calculate the remaining space value M of each partition according to the formula and Among them, F tbz The standard value of the remaining space for each equally divided area; F twz The residual spatial error value for each equally divided area.

[0138] Reduce the volume of the partially assembled cargo in the 4 equally divided areas until F tbz -K <F twz , optimization completed.

[0139] Volume replacement order: reduce the corresponding assembled cargo volume in the descending order of the assembled cargo volume and the ascending order of the assembled cargo importance.

[0140] Step 7: Planning and optimizing inbound and outbound routes.

[0141] S71. Collect historical data of each inbound and outbound operation, including cargo information, storage information, storage location, inbound and outbound paths, operation time and abnormal situations.

[0142] Cargo information: including cargo type, size, weight, quantity, type (such as fragile goods, refrigerated goods, etc.), access frequency, special requirements (such as temperature control, moisture-proof, shock-proof, etc.) and estimated arrival time.

[0143] Storage location: includes the specific storage location of the goods (such as shelf number, layer number, column number, etc.), as well as the attributes of the storage area (such as whether it is a refrigerated area, earthquake-proof area, etc.).

[0144] In and out of warehouse path: includes the actual path of each in and out of warehouse operation, records the driving route of the vehicle or handling equipment, the passages passed, the stop points, etc.

[0145] Operation time: includes the start time, end time and total time of each inbound and outbound operation.

[0146] Abnormal situations: record abnormal situations encountered during operation, such as equipment failure, channel blockage, human error, etc.

[0147] S72. Use machine learning algorithms (such as decision trees, neural networks, etc.) to analyze historical data and identify common patterns and regularities.

[0148] S73. Based on historical data and real-time conditions, predict future warehousing and outbound demand, and perform route planning and resource allocation in advance.

[0149] The goal is to minimize the operation efficiency while minimizing the operation time and resource consumption. The objective function is as follows:

[0150]

[0151] Where n is the number of targets; ω i is the weight of the i-th target; f i (x i ) is the cost function of the ith objective (such as path length, operation time, resource consumption, etc.); x i is the decision variable for the ith objective.

[0152] The constraints are the same as those in step 2 and will not be repeated here.

[0153] S74. Dynamically adjust the inbound and outbound routes to avoid congestion and conflict and improve operational efficiency.

[0154] Real-time monitoring: Use sensors and cameras to monitor warehouse operations in real time and obtain information such as current inventory status, channel occupancy, equipment operating status, etc.

[0155] Path replanning: If an abnormal situation is found (such as channel blockage, equipment failure, etc.), the system will immediately replan the path to ensure that the operation is not affected. For example, the shortest path algorithm (such as Dijkstra algorithm or A* algorithm) is used to recalculate the optimal path:

[0156] New Path=arg min(Path Length(p)+Obstacle Cost(p));

[0157] p∈All Paths;

[0158] Among them, Path Length(p) is the length of the path; Obstacle Cost(p) is the cost of the obstacle on the path.

[0159] Use online learning algorithms (such as incremental learning, stream learning, etc.) to update model parameters and adapt to the changing environment. Use the reward mechanism in reinforcement learning to encourage the system to choose a more efficient path:

[0160] Reward=α·Efficiency Gain+β·Safety Improvement;

[0161] Among them, α and β are weight coefficients, which respectively indicate the emphasis on efficiency and safety.

[0162] Step 8. Real-time monitoring and security management.

[0163] HD Camera and Sensor:

[0164] Install high-definition cameras and other sensors to monitor the operations inside the warehouse in real time, ensure that each vehicle maintains a safe distance (for example, 200 meters), and plan emergency evacuation routes in advance to inform each staff member how to evacuate quickly in an emergency.

[0165] Dynamic adjustment: When a transport vehicle has completed 80% of unloading, it notifies the next vehicle to prepare to enter the loading and unloading area to ensure a smooth and efficient warehousing process.

[0166] The beneficial effects of this embodiment are as follows: By means of intelligent 3D modeling, multi-scheme matching and evaluation, mathematical optimization and machine learning technologies, the efficiency of inbound and outbound operations is improved, the space and weight distribution are optimized, and the overall balance and safety of the warehouse are ensured. The system can dynamically adjust the path to avoid congestion and conflicts, monitor the operation situation in real time, respond quickly to exceptions, and ensure the safety of personnel and equipment. Efficient, intelligent and safe warehousing management is achieved, and the operation cost is reduced.

[0167] As mentioned above, the above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

[0168] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific embodiments. Obviously, many modifications and changes can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A system for planning the path of goods entering and leaving a warehouse, characterized in that: The system comprises Warehouse three-dimensional spatial structure establishment module: establish the warehouse's three-dimensional spatial structure according to the warehouse's shape and size parameters; divide the warehouse into multiple functional areas, including shelf areas, channel areas, and loading and unloading areas, with each functional area as an independent optimization unit; Storage menu generation and storage plan matching module: collect information about goods to be put into storage, generate storage menus, and assign unique identifiers to each type of goods; match multiple storage plans for each type of goods, evaluate the advantages and disadvantages of each plan, and select the best plan; Assignment and sorting module: Assign importance to each item in the storage menu. The larger the value, the more important the function of the item. Priority is assigned to the items according to the importance assigned, ensuring that important items are stored in the warehouse first and in an easily accessible location. Spatial weight calculation module: install each item in the three-dimensional spatial structure of the warehouse, calculate the remaining space value in the warehouse and the actual weight value of the warehouse as a whole; Calculate the balance coefficient to evaluate the balance status of warehouse space and weight; Space and weight optimization module: Determine whether space or weight optimization is needed based on the balance coefficient. If optimization is needed, adjust the distribution of goods in the warehouse to ensure the overall balance and stability of the warehouse; Inbound and outbound path planning optimization module: collects historical data of each inbound and outbound operation, analyzes common patterns and rules; predicts future inbound and outbound demand based on historical data and real-time conditions, and performs path planning and resource allocation in advance; monitors the operation status in the warehouse in real time, dynamically adjusts the inbound and outbound paths, avoids congestion and conflicts, and improves operation efficiency; Real-time monitoring management module: Install high-definition cameras and other sensors to monitor the operation status inside the warehouse in real time; Ensure that each vehicle maintains a safe distance and plan emergency evacuation routes in advance; dynamically adjust the operating process to ensure a smooth and efficient warehousing process.

2. A method for planning a path for entering and exiting a warehouse according to claim 1, characterized in that: The storage solutions include rack types, pallet types, stacking methods and other storage devices; Shelf types include heavy-duty shelves, medium-duty shelves, light-duty shelves, flow shelves and automated high-bay warehouses; pallet types include wooden pallets, plastic pallets and metal pallets; Stacking methods include single-layer stacking, multi-layer stacking, staggered stacking and gravity stacking; other storage equipment includes rotating racks, hanging storage and cold storage.

3. A method for planning the inbound and outbound paths of stored goods, used to implement the inbound and outbound path planning system for stored goods as claimed in claim 1, characterized in that: The method flow is as follows: Step 1: Establish the three-dimensional spatial structure of the warehouse. According to the shape and size parameters of the warehouse, use the three-dimensional modeling software to build the three-dimensional spatial structure of the warehouse and divide it into multiple functional areas, including shelf area, channel area, loading and unloading area, and each functional area is an independent optimization unit; Step 2: Generate a menu to be stored and match multiple storage solutions, including collecting cargo information, generating a menu to be stored, matching multiple storage solutions for each cargo, and evaluating the advantages and disadvantages of each storage solution; Step 3: Assign importance to the goods, assign values ​​to the goods according to their functional importance, and prioritize the goods according to the importance assigned, ensuring that important goods are given priority in storage and stored in easily accessible locations; record detailed information on each type of goods and the corresponding storage location, and store all goods information in the database for subsequent query and management; Step 4: Determine whether to optimize the space. By comparing the calculated balance coefficient with the preset threshold, decide whether to optimize the warehouse space and perform partition optimization. Step 5: Weight optimization: calculate the difference between the actual weight of the entire warehouse and the standard weight, and optimize the weight until the standard is met; Step 6: Space optimization: calculate the difference between the remaining space in the warehouse and the standard space, and optimize the space until the standard is met; Step 7: Planning and optimizing inbound and outbound routes: Collect historical data, use machine learning algorithms to analyze data, predict future inbound and outbound demand, and dynamically adjust inbound and outbound routes to avoid congestion and conflict. Step 8: Real-time monitoring and safety management: install high-definition cameras and sensors to monitor the internal operations of the warehouse in real time to ensure safe distances and emergency evacuation route planning.

4. A method for planning a path for entering and exiting a warehouse for stored goods according to claim 3, characterized in that: The evaluation in step 2 specifically includes: Build an optimization model and use mathematical programming methods to minimize the total cost and maximize space utilization and access efficiency. There are n storage solutions, and the evaluation indicators of each solution include storage cost, access convenience, security, space utilization, and flexibility. The objective function is as follows: Minimize Z =ω1C i +ω2A i +ω3S i -ω4U i -ω5F i ; Among them, C i is the cost of the i-th storage solution; A i is the access convenience of the i-th storage solution, expressed in time; S i is the security of the i-th storage solution, expressed as a risk score; U i is the space utilization of the i-th storage solution, expressed as a percentage; F i is the flexibility of the i-th storage solution, expressed as the adjustment ability score; ω1, ω2, ω3, ω4, ω5 are the evaluation indicators C i , A i , S i , U i 、F i The weight coefficient reflects the importance users attach to different evaluation indicators; The constraints are as follows: Space limit: The total available space V of the warehouse total Cannot exceed the actual capacity of the warehouse V max : Among them, V i is the space occupied by the i-th storage solution; x i is a binary variable (0 or 1) that selects the scheme; Access frequency requirements: For goods that are frequently accessed, the access time A i must be less than a certain threshold T threshold : A i ≤T threshold , Safety requirements: For fragile or dangerous goods, the safety risk S i must be below a certain threshold S threshold : S i ≤S threshold , Special storage requirements: For goods with special storage requirements, a storage solution that meets these requirements must be selected: if the goods require refrigeration, then i∈Refrigerated storage solution.

5. A method for planning a path for entering and exiting a warehouse for stored goods according to claim 3, characterized in that: The step 4 is as follows: Balance coefficient PH xs and the balance coefficient threshold PH min and PH max Conduct comparative analysis; if PH min <PH xs <PH max The warehouse space is not optimized; if PH xs ≤PH min or PH xs ≥PH max , then optimize the warehouse; Taking the main stress points of the warehouse as endpoints, divide the area formed by connecting these endpoints in sequence into y equal parts. Adjust the weight and remaining space of each partition in each divided area to ensure the overall balance and stability of the warehouse.

6. A method for planning a path for entering and exiting a warehouse for stored goods according to claim 3, characterized in that: The specific steps of step 5 are as follows: Calculate the actual weight value Z of the warehouse as a whole lz Compared with the warehouse standard weight value M bz The absolute value of the difference X mz and the weight error value M wz Compare; if X mz ≤M wz , the overall weight of the warehouse is not optimized; if X mz >M wz , then weight optimization is performed; Calculate the weight value M of each partition according to the formula and Among them, F mbz The standard weight value for each equally divided area; F mwz For each equally divided area, the weight error value is replaced by replacing the partially assembled goods in y equally divided areas until F mbz -M <F mwz , optimization completed; The corresponding goods are replaced in the order of increasing importance, from heavy goods to light goods.

7. A method for planning a path for entering and exiting a warehouse for stored goods according to claim 3, characterized in that: The specific steps of step 6 are as follows: Calculate the remaining space value K of each partition, and convert the remaining space value T in the warehouse into jz With warehouse standard space value T bz The absolute value of the difference T xz and spatial error value T wz For comparison; if T xz ≤T wz , then the remaining warehouse space is not optimized; if T xz >T wz , then space optimization is performed; The space optimization process is as follows: Calculate the remaining space value M of each partition according to the formula and Among them, F tbz The standard value of the remaining space for each equally divided area; F twz is the remaining space error value for each equally divided area; the volume of the partially assembled goods in y equally divided areas is reduced until F tbz -K <F twz , optimization is completed; the corresponding assembled cargo volume is reduced in the descending order of assembled cargo volume and the ascending order of assembled cargo importance.

8. A method for planning a path for entering and exiting a warehouse for stored goods according to claim 3, characterized in that: The step 7 also includes: minimizing the operation efficiency as the goal, while minimizing the operation time and resource consumption, the objective function is as follows: Where n is the number of targets; ω i is the weight of the i-th target; f i (x i ) is the cost function of the ith objective, including path length, operation time, and resource consumption; x i is the decision variable of the i-th objective; the constraints are consistent with those in step 2.

9. A method for planning a path for entering and exiting warehouse goods according to claim 3, characterized in that: The specific steps of step eight are as follows: installing high-definition cameras and other sensors to monitor the operation status inside the warehouse in real time, ensuring that each vehicle maintains a safe distance, and planning emergency evacuation routes in advance; when a transport vehicle completes a% of unloading, notifying the next vehicle to prepare to enter the loading and unloading area.

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