A process simulation method and system for a warehouse logistics system

Abstract

The application provides a warehouse logistics system process simulation method and system, relates to the technical field of logistics system simulation, and comprises the following steps: establishing a warehouse logistics system process simulation model; creating a resource use record table and a simulation task record table based on the process simulation model; determining resource information of each specific task in the process simulation model; calculating actual execution information of each specific task according to the resource information of each specific task, and recording task execution situation simulation calculation result information and resource use situation simulation calculation result information; and optimizing the resources through a heuristic bidirectional simulation resource optimization method. The traditional logistics system simulation method mostly adopts a discrete event simulation mode to accurately simulate all details, and problems such as low modeling efficiency, slow running speed and difficult model change exist in simulation. The process simulation model is established by adopting the method, and the simulation model is run through task driving.

Description

Technical Field

[0001] This invention relates to the field of logistics system simulation technology, and in particular to a process simulation method and system for warehousing and logistics systems. Background Technology

[0002] A warehousing and logistics system is a comprehensive system encompassing warehouse and inventory management, logistics transportation, order processing, and supply chain management. Based on the order tasks and processing requirements, the system processes orders according to a defined workflow to ensure the smooth flow and timely delivery of goods. This system requires workers, equipment, and sufficient space to support these activities. Therefore, it is a large-scale, integrated system comprised of people, machines, and space. Logistics activities are completed through the coordinated efforts of these elements, forming a specific operational process for each order task. The construction of a warehousing and logistics system involves high investment costs, and the system's efficiency needs to be evaluated based on the number of orders processed at different times to allow for adjustments and optimizations.

[0003] Logistics system simulation technology allows for the analysis of operational efficiency of real warehousing and logistics systems through computer-based simulation modeling and experiments, without altering the system's composition and operational mode. However, traditional logistics system simulation methods mostly employ discrete event simulation, often attempting to precisely simulate every detail. This approach suffers from low modeling efficiency, slow execution speed, and difficulty in modifying the model. Furthermore, decision-making based on simulation results frequently requires multiple rounds of simulation analysis and optimization. A sufficiently large number of simulation searches can lead to unbearable simulation time, further reducing the efficiency of simulation analysis and optimization of warehousing and logistics systems. Summary of the Invention

[0004] This invention provides a process-oriented simulation method and system for warehousing and logistics systems, which solves the problem in the prior art that when the number of simulation searches is too many, it leads to unbearable simulation time and reduces the efficiency of simulation analysis and optimization of warehousing and logistics systems.

[0005] To achieve the aforementioned objectives, the present invention provides the following technical solution: a process simulation method for a warehousing and logistics system, characterized in that the steps include:

[0006] S1. Obtain data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system;

[0007] S2. Based on the process-oriented simulation model, create a resource usage record table and a simulation task record table; perform preliminary calculations based on the input information.

[0008] S3. Obtain the calculation results and simulation task record table, and determine the process, activities, job objects, and resources required for each specific task in the process simulation model;

[0009] S4. Obtain the start time of each specific task and execute the tasks in the order of their start times.

[0010] S5. Obtain resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, calculate the actual execution information of each specific task, and record the simulation calculation results of task execution and resource usage.

[0011] S6. Optimize resources using a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation results.

[0012] Optionally, in step S1, the warehousing and logistics system data includes:

[0013] Warehousing and logistics system resources, processes, activities, work objects, resource usage, nodes, workflows, and task information;

[0014] Establishing a process-oriented simulation model for a warehousing and logistics system includes:

[0015] The system comprises the following modules: a resource module (defining the resources required by the warehousing and logistics system when processing tasks); a process module (defining the operational flow of the warehousing and logistics system); an activity module (defining whether the warehousing and logistics system can perform activities); an operation object module (defining the operation objects of the warehousing and logistics system); an activity resource usage module (defining the specific resources and quantities required by the warehousing and logistics system when performing an activity); a node module (defining the node areas of the warehousing and logistics system); a movement line module (defining the routes of the handling activities of the warehousing and logistics system); and a task module (recording the task information that the warehousing and logistics system needs to complete).

[0016] Optionally, in step S2, a resource usage record table and a simulation task record table are created based on the process-oriented simulation model; preliminary calculations are performed based on the input information, including:

[0017] Based on the resource information defined in the resource module of the process simulation model, a resource usage record table is generated for each specific resource defined in the resource module;

[0018] The resource usage record table records the simulation calculation results of resource usage in the warehousing and logistics system when performing a task.

[0019] Retrieve task information recorded in the task module and generate a simulation task record table;

[0020] Obtain the coordinate information of the nodes in the node module and calculate the distance of each movement line in the movement line module;

[0021] Get the speed information of resources in the resource module and the usage information of active resources in the active resource usage module;

[0022] Calculate the activity time for each specific transport activity in the activity module.

[0023] Optionally, in step S3, the calculation results and simulation task record table are obtained to determine the flow, activities, work objects, and resources required for each specific task in the process simulation model, including:

[0024] Based on the simulation task record table, obtain all incomplete tasks in the task module;

[0025] Execute tasks in the order of their executable time, and retrieve the activities that make up the process corresponding to the unfinished tasks in the process module;

[0026] Determine if all activities have been completed. If not, continue with the next unfinished task. Calculate the resources required for the activity. Start the activity when all resources are met, and use that time as the actual start time of the activity. If so, use the end time of the last activity as the actual end time of the task. Calculate the delay and write the task execution results into the simulation task record table.

[0027] Optionally, the calculation delay includes:

[0028] Obtain the actual start time of the first activity in each specific task, and treat the actual start time as the actual start time of the specific task.

[0029] Add the actual start time of the specific task to the duration of all activities of the specific task to obtain the planned completion time of the specific task.

[0030] Obtain the actual completion time of the last activity of a specific task, and regard the actual completion time as the actual completion time of the specific task;

[0031] The delay of a specific task is obtained by subtracting its planned completion time from its actual completion time.

[0032] Optionally, in step S5, based on the start time, flow, activities, resources required for each specific task, and resource usage, the actual execution information for each specific task is calculated, and the simulation results of task execution and resource usage are recorded, including:

[0033] Get the calculation results of all the resources required for the activity, read the activity resource usage module, and set resource constraint switches for each specific resource recorded in the resource module;

[0034] Select the resources required for a calculation activity, and determine whether the resource constraint switch is on. If it is on, the resources can only be used when all the required resources are met during the activity duration. If it is not on, the resources can be used as soon as the activity can start. If the number of resources exceeds the preset limit, the resource capacity is increased.

[0035] Optionally, in step S6, the heuristic bidirectional simulation resource optimization method includes:

[0036] A multi-round simulation optimization method for exploring resources with a fixed number of tasks, and a multi-round simulation optimization method for exploring tasks with a fixed amount of resources.

[0037] Optionally, a multi-round simulation optimization method for exploring resources with a fixed number of tasks includes:

[0038] Get a given task, set the optimal cycle for completing the given task, and use the satisfactory interval between the cycle and the completion time of the given task as the stopping condition for multiple rounds of simulation, and set the minimum resource quantity for each specific resource.

[0039] In the first round of simulation, the resource constraint switch is turned off, and the normalized resource utilization rate is multiplied by 100 and then rounded to obtain the initial value of the resource quantity.

[0040] Based on the initial value, the simulation iterates, and in each subsequent simulation, the resource constraint switch is turned on. The resource quantity for the next simulation is updated according to the ratio of the simulation task cycle to the set optimal cycle, based on the utilization rate or the resource quantity of the previous cycle, and the iteration continues until a satisfactory interval or other stopping conditions are reached.

[0041] Optionally, a multi-round simulation optimization method with a fixed number of exploration tasks using fixed resources includes:

[0042] Given the quantity of each type of resource and with the resource constraint switch turned off, the optimal task cycle and the satisfactory interval of task completion cycle are set as the stopping conditions for multiple rounds of simulation.

[0043] Set the planned task quantity or proportion for each type of task, randomly generate specific tasks in the task module, run the simulation and obtain the simulation results.

[0044] Based on the ratio of the simulation calculation task cycle to the set optimal cycle, adjust the planned task quantity for the next round of simulation and continue iterating until a satisfactory interval or other stopping conditions are reached.

[0045] A process simulation system for a warehousing and logistics system, the system being used in the aforementioned process simulation method for warehousing and logistics systems, the system comprising:

[0046] The model building unit is used to acquire data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system.

[0047] The preliminary calculation unit is used to create a resource usage record table and a simulation task record table based on the process simulation model; and to perform preliminary calculations based on the input information.

[0048] The task acquisition unit is used to acquire calculation results and simulation task record tables, and to determine the process, activities, job objects, and resources required for each specific task in the process simulation model.

[0049] The execution unit is used to obtain the start time of each specific task and execute the tasks in the order of their start times.

[0050] The simulation calculation unit is used to acquire resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, it calculates the actual execution information of each specific task and records the simulation calculation results of task execution and resource usage.

[0051] The optimization unit is used to optimize resources using a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation result information.

[0052] On the one hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the process simulation method of the above-mentioned warehousing and logistics system.

[0053] On the one hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the process simulation method of the above-mentioned warehousing and logistics system.

[0054] The above technical solution has at least the following advantages compared with the existing technology:

[0055] The above-described scheme, provided by this invention, divides the composition, layout, and processing tasks of a real warehousing and logistics system into resource, process, activity, work object, activity resource usage, node, movement line, and task modules for recording. It establishes a process-oriented simulation model of the warehousing and logistics system and runs the simulation in a task-driven manner. The process of each task is executed according to the order in which tasks can start and the system's resource usage. After all tasks are completed, the process-oriented simulation results are output. Based on this, by setting resource constraint switches, the upper limit of the number of resources required to complete a task without resource constraints can be simulated, and this upper limit can be used to measure resource bottlenecks. The heuristic bidirectional simulation resource optimization method can explore satisfactory solutions for the number of resources required to complete these tasks within a certain time under a limited number of simulations and a fixed number of tasks, as well as satisfactory solutions for the number of tasks the system can complete within a certain time under a fixed number of resources. The process-oriented simulation method for warehousing and logistics systems abandons the detailed modeling that has little impact on simulation results in traditional discrete event simulation modeling methods, reduces computational resource consumption, improves the efficiency of simulation modeling and simulation speed, and reduces the difficulty of modifying the simulation model, thereby further improving the efficiency of warehousing and logistics system simulation modeling, analysis, and optimization. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a schematic diagram of the process simulation method for a warehousing and logistics system provided in an embodiment of the present invention;

[0058] Figure 2 A schematic diagram of a process simulation model for a warehousing and logistics system provided in an embodiment of the present invention;

[0059] Figure 3 This is a schematic diagram of the process, activities, activity resource usage, and work objects in the process simulation method for warehousing and logistics systems provided in this embodiment of the invention.

[0060] Figure 4 This is a schematic diagram of nodes and movement lines in the process simulation method for warehousing and logistics systems provided in this embodiment of the invention.

[0061] Figure 5 This is a detailed process diagram illustrating the simulation calculation of resource usage in a process-oriented simulation method for warehousing and logistics systems provided in this embodiment of the invention.

[0062] Figure 6 This is a schematic diagram of the fixed-task resource exploration multi-round simulation optimization method in the process simulation method for warehousing and logistics systems provided in this embodiment of the invention.

[0063] Figure 7 This is a schematic diagram of the principle of the heuristic two-way simulation resource optimization method with a fixed amount of resources and a number of exploration tasks in the process simulation method for warehousing and logistics systems provided in this embodiment of the invention.

[0064] Figure 8 This is a block diagram of a process simulation system for a warehousing and logistics system provided in an embodiment of the present invention;

[0065] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0067] This invention addresses the problem in existing technologies where excessive simulation searches lead to unbearable simulation time, reducing the efficiency of simulation analysis and optimization of warehousing and logistics systems. It provides a process-oriented simulation method and system for warehousing and logistics systems.

[0068] like Figure 1 As shown, this embodiment of the invention provides a process simulation method for a warehousing and logistics system, which can be implemented by electronic devices. Figure 1 The flowchart shown is a process simulation method for a warehousing and logistics system. The processing flow of this method may include the following steps:

[0069] S101. Obtain data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system.

[0070] In one feasible implementation, in step S101, the warehousing and logistics system data includes:

[0071] Warehousing and logistics system resources, processes, activities, work objects, resource usage, nodes, workflows, and task information;

[0072] like Figure 2 As shown, establishing a process-oriented simulation model 200 for the warehousing and logistics system includes:

[0073] Resource module 210 defines the resources required by the warehousing and logistics system when processing tasks, and the resources have capacity limitations.

[0074] The process module 220 defines the operation process of the warehousing and logistics system, and each specific process has at least one specific activity;

[0075] The activity module 230 defines whether the warehousing and logistics system can perform activities. Activities are divided into two types: operational activities and handling activities. Each specific activity has a unique specific work object. The operation process defined in the process module consists of the activities defined in the activity module.

[0076] Module 240 defines the operation objects of the warehousing and logistics system.

[0077] Activity Resource Usage Module 250 defines the specific resources and quantities required for an activity in a warehousing and logistics system; activities are divided into two types: operational activities and handling activities.

[0078] Define node modules 260 for the operational areas of the warehousing and logistics system, and use several nodes to express the layout of the system;

[0079] Module 270 defines the movement path of material handling activities in a warehousing and logistics system;

[0080] Define task module 280 to record the task information that the warehousing and logistics system needs to complete. Each specific task has a unique specific operation process and operation object.

[0081] In one feasible implementation, for resource module 210, a real warehousing and logistics system needs to use several specific resources when performing a task, such as the space, workers, and logistics equipment resources required to execute the task process. To represent all the resources of a real warehousing and logistics system in the process simulation model, the resource module needs to define and record specific information for each resource. In this embodiment, the resource information parameters include: resource number, resource name, resource type, and available quantity. Further, the resource type refers to the type of specific resource that the process simulation model of the warehousing and logistics system needs to use when processing order tasks, including four types: personnel resources, equipment resources, space resources, and storage resources. Further, for personnel resources and equipment resources, the required input parameters include: speed; for storage resources, the required input parameters include: initial inventory.

[0082] For process module 220, a real warehousing and logistics system needs to follow a certain process to execute a task, and each task has a unique operation process. In order to represent all the operation processes that a real warehousing and logistics system can perform in the process simulation model of the warehousing and logistics system, the process module needs to record the specific process information for each process. In this embodiment of the invention, the process information parameters include: process number, process name, process type, and activity number that makes up the process. Furthermore, when a process consists of more than one activity, the activity numbers that make up the process are separated by semicolons. For example, to execute a receiving task, it is necessary to follow the receiving process, and the corresponding process information is recorded in process module 220.

[0083] For Activity Module 230, in a real warehousing and logistics system, a specific operational process consists of several activities; that is, an activity is the smallest unit that constitutes a specific operational process. To represent all the activities that a real warehousing and logistics system can perform in the simulation model, the Activity Module needs to record information for each specific activity. In this embodiment, the activity information parameters include: activity number, activity name, activity duration, work object number, and activity type. Further, the activity type is divided into two types: operational activities and handling activities. The activities constituting the process in the process module are composed of activity numbers defined in the Activity Module. Further, for the handling activity, the required input information includes: movement line number. For example, the receiving process consists of three activities: truck unloading, warehouse preparation, and warehouse transfer. Truck unloading and warehouse preparation are operational activities, while warehouse transfer is a handling activity, requiring the recording of movement line numbers. These activities all belong to the receiving process. The Activity Module 230 records the information of these activities, and the Process Module 220 records the activity number information constituting the process in the corresponding receiving process, separating each activity number with a semicolon.

[0084] For the task object module 240, in a real warehousing and logistics system, each specific task and activity has a unique task object. That is, the execution object of a task or activity is a specific task object. To represent the task objects of a real warehousing and logistics system in the process simulation model, the task object module 240 needs to record information for each specific task object. In this embodiment, the task object information parameters include: task object number and task object name. Furthermore, the activity task objects in the activity module are all composed of task object numbers defined in the task object module. For example, the task object for a truck unloading activity is the truck, and the task object for inbound preparation and inbound transfer activities is the pallet. The task object module 240 records the corresponding task object information, and the activity module 230 records the corresponding task object number information from the task object module 240 in the task object number of the corresponding activity.

[0085] For the activity resource usage module 250, in order to express the specific resources and quantities required for each specific activity in the real warehousing and logistics system in the process simulation model of the warehousing and logistics system, the activity resource usage module needs to record the resource usage information for each activity. In this embodiment of the invention, the activity resource usage parameters include: resource number, activity number, and the quantity of specific resources used. Further, the resource number in the activity resource usage module 250 is composed of the resource number recorded in the resource module 210; the activity number is composed of the activity number recorded in the activity module 230. For example, an inbound transfer activity requires one worker to use one forklift. The activity resource usage module 250 records the inbound transfer activity number information recorded in the activity module 230, as well as the worker resource number information and forklift resource number information recorded in the resource module 210.

[0086] For node module 260, in a real warehousing and logistics system, activities need to be carried out in a certain work area, or moved from one work area to another. To represent the layout and work areas of a real warehousing and logistics system in the process simulation model, the node module needs to record node information representing each work area. In this embodiment, the node information parameters include: node number, node name, node type, and node coordinates. Further, the node type is divided into two types: work nodes and transport nodes. In the activity module, activities of type work occur at work nodes defined in the work node module; activities of type transport occur between work nodes or between a work node and a transport node. The node coordinates are the three-dimensional spatial coordinates of the node in the warehousing and logistics system. For example, the inbound preparation activity is a work activity that occurs in the inbound buffer area of ​​the warehousing and logistics system. A node is used to represent the inbound buffer area, and the node module 260 records the corresponding node information.

[0087] For the movement module 270, in order to represent the handling routes of handling activities in the real warehousing and logistics system in the process simulation model of the warehousing and logistics system, in this embodiment of the invention, the movement parameters include: path number, path start node, path end node, path distance, movement line number, movement line name, and movement line distance. Further, the path start node and path end node are composed of node numbers defined in the node module 250; the path distance is obtained by calculating the Manhattan distance between nodes based on the node coordinates of the path start node and path end node; the movement line distance is obtained by adding the distances of all paths that make up the movement line, since each movement line consists of at least one path; each handling activity defined in the activity module 230 has a unique movement line defined in the movement module 250. For example, the inbound transfer activity belongs to the handling activity, which moves goods from the inbound buffer area of ​​the warehousing and logistics system to the shelf storage area. Movement lines are used to represent the routes where the handling activities occur, and the movement module 250 records the corresponding movement line information.

[0088] Obtain the coordinate information of the nodes in the node module 260, calculate the distance of each movement line in the movement line module 270; after the distance of the movement line is calculated, obtain the speed information of the resources in the resource module 210, the activity resource usage information in the activity resource usage module 250, and calculate the activity time of each specific transportation activity in the activity module 230.

[0089] For task module 280, in order to represent the tasks in the real warehousing and logistics system in the process simulation model of the warehousing and logistics system, the task module needs to record the information of each specific task. In this embodiment of the invention, the task information parameters include: task number, task type, process number, process name, work object number, work object name, and task start time. Furthermore, different task types require different information when being processed; therefore, task module 280 also needs to record the specific information required to process the task according to different task types. The process number and process name of task module 280 are composed of the process number and process name defined in process module 220. The work object number and work object name of task module 280 are composed of the work object number and work object name defined in work object module 240. The tasks in the task module are arranged in the order of their start times, with tasks with earlier start times arranged first and tasks with later start times arranged last.

[0090] One feasible implementation method is, for example Figure 3 As shown, this warehousing and logistics system needs to perform five types of tasks: receiving tasks, warehouse transfer tasks, picking tasks, sorting tasks, and shipping tasks. Different types of tasks correspond to different types of processes. Figure 4Taking the receiving task as an example, this type of task has three processes: receiving into a flat warehouse, receiving into a high-bay warehouse, and receiving into a forklift beam warehouse. Each process consists of several activities, which are recorded in the activity module 230. The work objects of the activities are recorded in the work object module 240, and the resource information used by the activities is recorded in the activity resource usage module 250. Activities are used to form different processes when establishing the process simulation model of the warehousing and logistics system and are recorded in the process module 220. Each process of the warehousing and logistics system has several resources for executing these tasks, which are recorded in the resource module 210.

[0091] like Figure 4 As shown, taking the receiving and storage process in a high-bay warehouse as an example, operation nodes are used to represent the layout and operation areas of the warehousing and logistics system. Operational activities are considered to be performed at operation nodes, and handling activities are considered to be moving objects from one operation node to another. Movement lines are used to define the handling routes. Handling nodes can be defined at appropriate locations according to the actual layout of the warehousing and logistics system to bypass obstacles or set specific movement lines. This node information is recorded in node module 260, and movement line information is recorded in movement line module 270.

[0092] S102. Based on the process-oriented simulation model, create a resource usage record table and a simulation task record table; perform preliminary calculations based on the input information.

[0093] In one feasible implementation, in step S102, a resource usage record table and a simulation task record table are created based on the process-oriented simulation model; preliminary calculations are performed based on the input information, including:

[0094] Based on the resource information defined in the resource module of the process simulation model, a resource usage record table is generated for each specific resource defined in the resource module;

[0095] The resource usage record table records the simulation calculation results of resource usage in the warehousing and logistics system when performing a task.

[0096] Retrieve task information recorded in the task module and generate a simulation task record table;

[0097] Obtain the coordinate information of the nodes in the node module and calculate the distance of each movement line in the movement line module;

[0098] Get the speed information of resources in the resource module and the usage information of active resources in the active resource usage module;

[0099] Calculate the activity time for each specific transport activity in the activity module.

[0100] One feasible implementation method is, for example Figure 1As shown, based on the resource information defined in the process simulation model resource module 210, a resource usage record table is generated for each specific resource defined in the resource module. The resource usage record table is used to record the simulation calculation results of resource usage when the warehousing and logistics system performs a task. In this embodiment, the resource usage record information parameters include: resource number, resource name, task number, task name, activity number, activity name, status, status change time, resource quantity used at the time of status change, resource capacity, and change amount. Furthermore, the states include two types: resource occupancy state and resource release state. Resource occupancy state indicates that a task in the warehousing and logistics system occupies a specific resource while performing an activity, and resource release state indicates that a task in the warehousing and logistics system releases a specific resource upon completing an activity. The state change time refers to the specific moment when the resource occupancy state or resource release state occurs. The resource quantity used at the state change time refers to the quantity of a specific resource used at a given state change time. The change amount refers to the quantity of a specific resource occupied when the resource occupancy state occurs, and the quantity of a specific resource released when the resource release state occurs. The resource usage information in the resource usage record table is arranged in chronological order according to the state change times.

[0101] S103. Obtain the calculation results and simulation task record table, and determine the process, activities, job objects, and resources required for each specific task in the process simulation model.

[0102] In one feasible implementation, step S103 involves obtaining the calculation results and simulation task record table to determine the flow, activities, work objects, and resources required for each specific task in the process simulation model, including:

[0103] Based on the simulation task record table, obtain all incomplete tasks in the task module;

[0104] Execute tasks in the order of their executable time, and retrieve the activities that make up the process corresponding to the unfinished tasks in the process module;

[0105] Determine if all activities have been completed. If not, continue with the next unfinished task. Calculate the resources required for the activity. Start the activity when all resources are met, and use that time as the actual start time of the activity. If so, use the end time of the last activity as the actual end time of the task. Calculate the delay and write the task execution results into the simulation task record table.

[0106] In one feasible implementation, when executing a specific task, it is necessary to obtain the resource usage records in the resource usage record table. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, the actual start time, planned completion time, actual completion time, delay, and the time and quantity of a specific resource used for each specific task are calculated. The simulation calculation results of the task execution status are written into the simulation task record table, and the simulation calculation results of the resource usage status are written into the resource usage record table.

[0107] In one feasible implementation, the actual start time of each activity in each specific task must meet the condition that at that moment, all resources required by the first activity of the task's operation process can be fully satisfied from the actual start time of the activity to the actual completion time of the activity.

[0108] The actual start time of each activity in each specific task is calculated as follows:

[0109] Taking the start time of the specific task as the current time, by reading the resource usage record table corresponding to the required resources, and based on the information of the state change time, the number of resources used at the state change time, and the resource capacity in the resource usage record, it is determined whether the number of resources used from the current time to the end time of the activity, plus the number of resources required to execute the activity, is less than or equal to the resource capacity.

[0110] If the current time is less than or equal to the total resource capacity, then the current time can be taken as the actual start time of the activity;

[0111] If the resource usage exceeds the capacity of one of the resources, find the resource usage record where the sum of the resources required to execute the activity is greater than the resource capacity. Read the first record after that record where the resource usage is less than the resource capacity. Use the state change time of that record as the new current time. Continue to calculate whether the resource usage requirements are met at that time until a time that meets all resource usage requirements is found. Use that time as the actual start time of the activity.

[0112] In one feasible implementation, the actual start time of the first activity of each specific task can be regarded as the actual start time of the task; adding the actual start time of the task to the duration of all activities of the task can yield the planned completion time of the task; the actual completion time of the last activity of the task can be regarded as the actual completion time of the task; subtracting the planned completion time of the task from the actual completion time of the task can yield the delay of the task.

[0113] In one possible implementation, calculating the delay includes:

[0114] Obtain the actual start time of the first activity in each specific task, and treat the actual start time as the actual start time of the specific task.

[0115] Add the actual start time of the specific task to the duration of all activities of the specific task to obtain the planned completion time of the specific task.

[0116] Obtain the actual completion time of the last activity of a specific task, and regard the actual completion time as the actual completion time of the specific task;

[0117] The delay of a specific task is obtained by subtracting its planned completion time from its actual completion time.

[0118] In one feasible implementation, a simulation task record table is generated based on the task information recorded in the process simulation model task module 280. The simulation task record table is used to record task execution information when the process simulation model of the warehousing and logistics system executes a task. In this embodiment, the simulation task record information parameters, in addition to the parameters of the task information in the process simulation model task module 280, also include: the actual start time of the task, the planned completion time of the task, the actual completion time of the task, and the delay. Further, the actual start time of the first activity of each specific task can be considered as the actual start time of the task; adding the actual start time of the task to the duration of all activities of the task yields the planned completion time of the task; the actual completion time of the last activity of the task can be considered as the actual completion time of the task; subtracting the planned completion time of the task from the actual completion time of the task yields the delay of the task.

[0119] S104. Obtain the start time of each specific task and execute the tasks in the order of their start times.

[0120] S105. Obtain resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, calculate the actual execution information of each specific task, and record the simulation calculation results of task execution and resource usage.

[0121] In one feasible implementation, in step S105, based on the start time, flow, activities, resources required for each specific task, and resource usage, the actual execution information of each specific task is calculated, and the simulation calculation results of task execution and resource usage are recorded, including:

[0122] Get the calculation results of all the resources required for the activity, read the activity resource usage module, and set resource constraint switches for each specific resource recorded in the resource module;

[0123] Select the resources required for a calculation activity, and determine whether the resource constraint switch is on. If it is on, the resources can only be used when all the required resources are met during the activity duration. If it is not on, the resources can be used as soon as the activity can start. If the number of resources exceeds the preset limit, the resource capacity is increased.

[0124] One feasible implementation method is, for example Figure 5 As shown, this receiving task requires executing a receiving and storage process, which consists of two activities: receiving preparation and transporting to the automated warehouse. Receiving preparation is a work activity requiring 1 forklift and 1 receiving clerk, with a duration of 3 minutes. Transporting to the automated warehouse is a transport activity requiring 1 automated guided vehicle (AGV), with a duration of 2 minutes. The task can start at 10:00, and all resource constraint switches are enabled. Using the process simulation method, the resource usage records for the forklift and receiving clerk required for the first activity are read. The task start time is added to the activity duration. During this time, the required resource quantity is added. The forklift usage is less than the resource capacity, while the receiving clerk usage is greater than the resource capacity. Therefore, starting from 10:00, the first record where the receiving clerk usage is less than the resource capacity is identified as the new activity start time of 10:10. At 10:10 AM, both forklift resources and receiving personnel resources meet the condition of being less than or equal to the resource capacity. Therefore, 10:10 AM is taken as the actual start time of the inbound preparation activity, and the actual completion time of this activity is calculated to be 10:13 AM. The resource usage is recorded in the resource usage record table. Since the inbound preparation activity is the first activity of this task, 10:10 AM is taken as the start time of the task. After the first activity is completed, the second activity of the task flow continues to be executed. The actual completion time of the first activity, 10:13 AM, is taken as the start time of the second activity. Using the aforementioned process simulation method, this continues until all activities of the task flow are completed. The actual completion time of the last activity, 10:15 AM, is taken as the actual completion time of the task. The task simulation calculation results are recorded in the simulation task record table.

[0125] Furthermore, in the above embodiment, the resource constraint switch for receiving personnel resources is set to off, and a process-based simulation method is used to calculate the specific receiving task. When the calculated number of receiving personnel resources used exceeds the resource capacity, the resource capacity of the receiving personnel will be increased, and time 10 will be directly used as the start time of the activity. The resource usage information will then be written into the resource usage record table.

[0126] Once all tasks in task module 280 have been completed, the simulation ends and the simulation results are output.

[0127] S106. Optimize resources using a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation results.

[0128] In one feasible implementation, step S106, the heuristic bidirectional simulation resource optimization method includes:

[0129] A multi-round simulation optimization method for exploring resources with a fixed number of tasks, and a multi-round simulation optimization method for exploring tasks with a fixed amount of resources.

[0130] One feasible implementation method is, for example Figure 6 As shown, the multi-round simulation optimization method for exploring resources with a fixed number of tasks includes:

[0131] Get a given task, set the optimal cycle for completing the given task, and use the satisfactory interval between the cycle and the completion time of the given task as the stopping condition for multiple rounds of simulation, and set the minimum resource quantity for each specific resource.

[0132] In the first round of simulation, the resource constraint switch is turned off, and the normalized resource utilization rate is multiplied by 100 and then rounded to obtain the initial value of the resource quantity.

[0133] Based on the initial value, the simulation iterates, and in each subsequent simulation, the resource constraint switch is turned on. The resource quantity for the next simulation is updated according to the ratio of the simulation task cycle to the set optimal cycle, based on the utilization rate or the resource quantity of the previous cycle, and the iteration continues until a satisfactory interval or other stopping conditions are reached.

[0134] In one feasible implementation, a fixed-task resource quantity exploration multi-round simulation optimization method is used. In this embodiment, a warehousing and logistics system has three types of resources and needs to complete several tasks. The method explores the quantity of each specific resource required to complete these tasks within a time range of 24 hours (the optimal task completion period) and 23.5 to 24.5 hours (a satisfactory task completion period). A minimum resource quantity for each specific resource is also set. Using this fixed-task resource quantity exploration multi-round simulation optimization method, through multiple rounds of process simulation, iteration stops when the calculated task completion period is within the satisfactory range or the upper limit of the simulation iteration count is reached, and the simulation results are output.

[0135] In the first simulation, the resource constraint switch is turned off, and the normalized resource utilization rate is multiplied by 100 and rounded to obtain the initial resource quantity. Assuming the task completion period for the first simulation is 8 hours, and the utilization rates of the three resources are 15%, 24%, and 9% respectively, the initial resource capacities are 15, 24, and 9 respectively. Therefore, in the second simulation, the resource capacities for the three resources will be set to 15, 24, and 9 respectively, and the resource constraint switch will be turned on. Assuming the task completion period for the second simulation is 16 hours, the ratio to the optimal task completion period is 2:3. Therefore, in the third simulation, the resource capacities for the three resources will be set to two-thirds of those in the second simulation, i.e., 10, 16, and 6 respectively. The simulation continues to calculate the ratio of the task completion period to the set optimal task completion period. The resource capacities from the previous round are multiplied by this ratio, and the resource quantity for the next simulation is updated and iterated until a satisfactory interval or other stopping condition is reached.

[0136] One feasible implementation method is, for example Figure 7 As shown, the multi-round simulation optimization method for the number of exploration tasks with fixed resource quantity includes:

[0137] Given the quantity of each type of resource and with the resource constraint switch turned off, the optimal task cycle and the satisfactory interval of task completion cycle are set as the stopping conditions for multiple rounds of simulation.

[0138] Set the planned task quantity or proportion for each type of task, randomly generate specific tasks in the task module, run the simulation and obtain the simulation results.

[0139] Based on the ratio of the simulation calculation task cycle to the set optimal cycle, adjust the planned task quantity for the next round of simulation and continue iterating until a satisfactory interval or other stopping conditions are reached.

[0140] In one feasible implementation, a warehousing and logistics system has three types of resources and four task processing flows, with the ratio of the four tasks being 1:2:3:4. The capacities of the three resources are fixed at 15, 24, and 9 respectively. A resource constraint switch is enabled to explore the maximum number of tasks that these resources can complete within a time range of 24 hours (optimal task completion period) and 23.5 to 24.5 hours (satisfactory task completion period). A multi-round simulation optimization method with fixed resource quantities is used to explore the number of tasks. A certain number of tasks are randomly generated according to the ratio of the four tasks. Assuming the total number of generated tasks is 100, the number of the four tasks are 10, 20, 30, and 40 respectively. The task cycle is calculated using a process-based simulation method. Assuming the task cycle calculated in the first round is 12 hours, the ratio of this to the optimal task cycle is 1:2. Therefore, in the second round of simulation, the total number of tasks will be doubled compared to the first round, and the number of the four types of tasks will be set to 20, 40, 60, and 80 respectively. The simulation continues to calculate the ratio of the task completion cycle to the set optimal task completion cycle. The total number of tasks from the previous round is divided by this ratio, and the total number of tasks for the next round of simulation is updated. The iteration continues until a satisfactory interval or other stopping conditions are reached.

[0141] In this embodiment of the invention, the composition, layout, and processing tasks of a real warehousing and logistics system are divided into resource, process, activity, work object, activity resource usage, node, movement line, and task modules for recording. A process-oriented simulation model of the warehousing and logistics system is established, and the simulation is run in a task-driven manner. The process of each task is executed according to the order in which tasks can start and the system's resource usage. After all tasks are completed, the process-oriented simulation results are output. Based on this, by setting resource constraint switches, the upper limit of the number of resources required to complete a task without resource constraints can be simulated, and this upper limit is used to measure resource bottlenecks. The heuristic bidirectional simulation resource optimization method can explore a satisfactory solution for the number of resources required for the system to complete these tasks within a certain time under a limited number of simulations and a fixed number of tasks, and also explore a satisfactory solution for the number of tasks the system can complete within a certain time under a fixed number of resources. The process-oriented simulation method for warehousing and logistics systems abandons the detailed modeling that has little impact on the simulation results in traditional discrete event simulation modeling methods, reduces the consumption of computational resources, improves the efficiency of simulation modeling and simulation speed, and reduces the difficulty of modifying the simulation model, thereby further improving the efficiency of warehousing and logistics system simulation modeling, analysis, and optimization.

[0142] Figure 8 This is a schematic diagram of a process simulation system for a warehousing and logistics system according to the present invention. The system 300 is used in the above-mentioned process simulation method for the warehousing and logistics system, and the system 300 includes:

[0143] Model building unit 310 is used to acquire data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system.

[0144] The preliminary calculation unit 320 is used to create a resource usage record table and a simulation task record table based on the process simulation model; and to perform preliminary calculations based on the input information.

[0145] The task acquisition unit 330 is used to acquire calculation results and simulation task record tables, and to determine the process, activities, job objects, and resources required for each specific task in the process simulation model.

[0146] The execution unit 340 is used to obtain the start time of each specific task and execute the tasks in the order of their start times.

[0147] The simulation calculation unit 350 is used to acquire resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, it calculates the actual execution information of each specific task and records the simulation calculation results of task execution and resource usage.

[0148] The optimization unit 360 is used to optimize resources through a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation result information.

[0149] Optionally, warehousing and logistics system data includes:

[0150] Warehousing and logistics system resources, processes, activities, work objects, resource usage, nodes, workflows, and task information;

[0151] Establishing a process-oriented simulation model for a warehousing and logistics system includes:

[0152] The system comprises the following modules: a resource module (defining the resources required by the warehousing and logistics system when processing tasks); a process module (defining the operational flow of the warehousing and logistics system); an activity module (defining whether the warehousing and logistics system can perform activities); an operation object module (defining the operation objects of the warehousing and logistics system); an activity resource usage module (defining the specific resources and quantities required by the warehousing and logistics system when performing an activity); a node module (defining the node areas of the warehousing and logistics system); a movement line module (defining the routes of the handling activities of the warehousing and logistics system); and a task module (recording the task information that the warehousing and logistics system needs to complete).

[0153] Optionally, the preliminary calculation unit 320 is used to generate a resource usage record table for each specific resource defined in the resource module based on the resource information defined in the process simulation model resource module;

[0154] The resource usage record table records the simulation calculation results of resource usage in the warehousing and logistics system when performing a task.

[0155] Retrieve task information recorded in the task module and generate a simulation task record table;

[0156] Obtain the coordinate information of the nodes in the node module and calculate the distance of each movement line in the movement line module;

[0157] Get the speed information of resources in the resource module and the usage information of active resources in the active resource usage module;

[0158] Calculate the activity time for each specific transport activity in the activity module.

[0159] Optionally, the task acquisition unit 330 is used to acquire all unfinished tasks of the task module according to the simulation task record table;

[0160] Execute tasks in the order of their executable time, and retrieve the activities that make up the process corresponding to the unfinished tasks in the process module;

[0161] Determine if all activities have been completed. If not, continue with the next unfinished task. Calculate the resources required for the activity. Start the activity when all resources are met, and use that time as the actual start time of the activity. If so, use the end time of the last activity as the actual end time of the task. Calculate the delay and write the task execution results into the simulation task record table.

[0162] Optionally, the calculation delay includes:

[0163] Obtain the actual start time of the first activity in each specific task, and treat the actual start time as the actual start time of the specific task.

[0164] Add the actual start time of the specific task to the duration of all activities of the specific task to obtain the planned completion time of the specific task.

[0165] Obtain the actual completion time of the last activity of a specific task, and regard the actual completion time as the actual completion time of the specific task;

[0166] The delay of a specific task is obtained by subtracting its planned completion time from its actual completion time.

[0167] Optionally, the simulation calculation unit 350 is used to obtain the calculation results of all resources required for the activity, read the activity resource usage module, and set resource constraint switches for each specific resource recorded in the resource module;

[0168] Select the resources required for a calculation activity, and determine whether the resource constraint switch is on. If it is on, the resources can only be used when all the required resources are met during the activity duration. If it is not on, the resources can be used as soon as the activity can start. If the number of resources exceeds the preset limit, the resource capacity is increased.

[0169] Optionally, the optimization unit 360 is used for multi-round simulation optimization of resource quantity exploration with a fixed number of tasks, and multi-round simulation optimization of resource quantity exploration task quantity.

[0170] Optionally, a multi-round simulation optimization method for exploring resources with a fixed number of tasks includes:

[0171] Get a given task, set the optimal cycle for completing the given task, and use the satisfactory interval between the cycle and the completion time of the given task as the stopping condition for multiple rounds of simulation, and set the minimum resource quantity for each specific resource.

[0172] In the first round of simulation, the resource constraint switch is turned off, and the normalized resource utilization rate is multiplied by 100 and then rounded to obtain the initial value of the resource quantity.

[0173] Based on the initial value, the simulation iterates, and in each subsequent simulation, the resource constraint switch is turned on. The resource quantity for the next simulation is updated according to the ratio of the simulation task cycle to the set optimal cycle, based on the utilization rate or the resource quantity of the previous cycle, and the iteration continues until a satisfactory interval or other stopping conditions are reached.

[0174] Optionally, a multi-round simulation optimization method with a fixed number of exploration tasks using fixed resources includes:

[0175] Given the quantity of each type of resource and with the resource constraint switch turned off, the optimal task cycle and the satisfactory interval of task completion cycle are set as the stopping conditions for multiple rounds of simulation.

[0176] Set the planned task quantity or proportion for each type of task, randomly generate specific tasks in the task module, run the simulation and obtain the simulation results.

[0177] Based on the ratio of the simulation calculation task cycle to the set optimal cycle, adjust the planned task quantity for the next round of simulation and continue iterating until a satisfactory interval or other stopping conditions are reached.

[0178] In this embodiment of the invention, the system provides a process-oriented simulation model of the warehousing and logistics system. This model is divided into resource, process, activity, work object, activity resource usage, node, movement line, and task modules for recording. The simulation is then run in a task-driven manner. Each task's process is executed according to its start time sequence and the system's resource usage. After all tasks are completed, the process-oriented simulation results are output. Furthermore, by setting resource constraint switches, the upper limit of the resources required to complete a task without resource constraints can be simulated, and this upper limit can be used to measure resource bottlenecks. A heuristic bidirectional simulation resource optimization method can explore satisfactory solutions for the number of resources required to complete these tasks within a certain time under a limited number of simulations and a fixed number of tasks, as well as satisfactory solutions for the number of tasks the system can complete within a certain time under a fixed number of resources. This process-oriented simulation method for warehousing and logistics systems eliminates the detailed modeling that has little impact on simulation results in traditional discrete event simulation modeling methods, reducing computational resource consumption, improving simulation modeling efficiency and running speed, and reducing the difficulty of modifying the simulation model. This further improves the efficiency of warehousing and logistics system simulation modeling, analysis, and optimization.

[0179] Figure 9 This is a schematic diagram of the structure of an electronic device 400 provided in an embodiment of the present invention. The electronic device 400 can vary considerably due to differences in configuration or performance. It may include one or more central processing units (CPUs) 401 and one or more memories 402. The memory 402 stores at least one instruction, which is loaded and executed by the processor 401 to implement the steps of the following process simulation method for a warehousing and logistics system:

[0180] S1. Obtain data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system;

[0181] S2. Based on the process-oriented simulation model, create a resource usage record table and a simulation task record table; perform preliminary calculations based on the input information.

[0182] S3. Obtain the calculation results and simulation task record table, and determine the process, activities, job objects, and resources required for each specific task in the process simulation model;

[0183] S4. Obtain the start time of each specific task and execute the tasks in the order of their start times.

[0184] S5. Obtain resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, calculate the actual execution information of each specific task, and record the simulation calculation results of task execution and resource usage.

[0185] S6. Optimize resources using a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation results.

[0186] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including instructions that can be executed by a processor in a terminal to complete the process simulation method of the aforementioned warehousing and logistics system. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0187] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

Claims

1. A process-based simulation method for a warehousing and logistics system, characterized in that, The method steps include: S1. Obtain data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system; The process simulation model for establishing the warehousing and logistics system includes: The system includes: a resource module that defines the resources required by the warehousing and logistics system when processing tasks; a process module that defines the operation flow of the warehousing and logistics system; an activity module that defines whether the warehousing and logistics system can perform activities; an operation object module that defines the work objects of the warehousing and logistics system; an activity resource usage module that defines the specific resources and quantities required by the warehousing and logistics system when performing an activity; a node module that defines the work area of ​​the warehousing and logistics system; a flow module that defines the routes of the handling activities of the warehousing and logistics system; and a task module that records the task information that the warehousing and logistics system needs to complete. S2. Based on the process simulation model, create a resource usage record table and a simulation task record table; perform preliminary calculations based on the input information; S3. Obtain the calculation results and simulation task record table, and determine the process, activities, job objects, and resources required for each specific task in the process simulation model. S4. Obtain the start time of each specific task and execute the tasks in the order of their start times. S5. Obtain resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, calculate the actual execution information of each specific task, and record the simulation calculation results of task execution and resource usage. S6. Optimize resources using a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs the simulation results. Heuristic two-way simulation resource optimization methods include: A multi-round simulation optimization method for exploring resources with a fixed number of tasks, and a multi-round simulation optimization method for exploring tasks with a fixed amount of resources; A multi-round simulation optimization method for exploring resources with a fixed number of tasks includes: Obtain a given task, set the optimal cycle for completing the given task, and use the satisfactory interval between the cycle of completing the given task as the stopping condition for multiple rounds of simulation, and set the minimum resource quantity for each specific resource; In the first round of simulation, the resource constraint switch is turned off, and the normalized resource utilization rate is multiplied by 100 and then rounded to obtain the initial value of the resource quantity. Based on the initial value, the simulation iterates, and in each subsequent simulation, the resource constraint switch is turned on. The resource quantity for the next simulation is updated according to the ratio of the simulation task cycle to the set optimal cycle, based on the utilization rate or the resource quantity of the previous cycle, and the iteration continues until a satisfactory interval or other preset stopping conditions are reached. A multi-round simulation optimization method for the number of exploration tasks with fixed resource quantities includes: Given the quantity of each type of resource and with the resource constraint switch turned off, set the optimal task cycle and the satisfactory interval of task completion cycle as the stopping condition for multiple rounds of simulation; Set the planned task quantity or proportion for each type of task, randomly generate specific tasks in the task module, run the simulation and obtain the simulation results. Based on the ratio of the simulation calculation task cycle to the set optimal cycle, adjust the planned task quantity for the next round of simulation and continue iterating until a satisfactory interval or other stopping conditions are reached.

2. The method according to claim 1, characterized in that, In step S1, the warehousing and logistics system data includes: Warehousing and logistics system resources, processes, activities, work objects, resource usage, nodes, workflows, and task information.

3. The method according to claim 2, characterized in that, In step S2, based on the process-oriented simulation model, a resource usage record table and a simulation task record table are created; preliminary calculations are performed based on the input information, including: Based on the resource information defined in the process simulation model resource module, a resource usage record table is generated for each specific resource defined in the resource module. The resource usage record table records the simulation calculation results of resource usage in the warehousing and logistics system when performing a task. Retrieve task information recorded in the task module and generate a simulation task record table; Obtain the coordinate information of the nodes in the node module and calculate the distance of each movement line in the movement line module; Get the speed information of resources in the resource module and the usage information of active resources in the active resource usage module; Calculate the activity time for each specific transport activity in the activity module.

4. The method according to claim 3, characterized in that, In step S3, the calculation results and simulation task record table are obtained, and the flow, activities, work objects, and resources required for each specific task in the process simulation model are determined, including: Based on the simulation task record table, obtain all unfinished tasks of the task module; Execute the tasks in the order of their executable times, and obtain the activities of the constituent processes corresponding to the unfinished tasks in the process module; Determine whether all activities have been completed. If not, continue to execute the next unfinished task, calculate the resources required for the activity, and start the activity when all resources are met. Use the time when all resources are met as the actual start time of the activity. If so, use the end time of the last activity as the actual end time of the task, calculate the delay, and write the task execution result into the simulation task record table.

5. The method according to claim 3, characterized in that, The computational delay includes: Obtain the actual start time of the first activity of each specific task, and regard the actual start time as the actual start time of the specific task. Add the actual start time of the specific task to the duration of all activities of the specific task to obtain the planned completion time of the specific task. Obtain the actual completion time of the last activity of the specific task, and regard the actual completion time as the actual completion time of the specific task; The delay of the specific task is obtained by subtracting its planned completion time from its actual completion time.

6. The method according to claim 5, characterized in that, In step S5, based on the start time, flow, activities, resources required for each specific task, and resource usage, the actual execution information for each specific task is calculated, and the simulation results of task execution and resource usage are recorded, including: Get the calculation results of all the resources required for the activity, read the activity resource usage module, and set resource constraint switches for each specific resource recorded in the resource module; Select the resources required for a calculation activity, and determine whether the resource constraint switch is on. If it is on, the required resources can only be used when all the required resources are met during the activity duration. If it is not on, the resources can be used as soon as the activity can start. If the number of resources exceeds the preset limit, the resource capacity is increased.

7. A process simulation system for a warehousing and logistics system, characterized in that, The system is used in the process simulation method for the warehousing and logistics system as described in any one of claims 1 to 6, and the system includes: The model building unit is used to acquire data from the warehousing and logistics system and establish a process simulation model of the warehousing and logistics system. The preliminary calculation unit is used to create a resource usage record table and a simulation task record table based on the process simulation model; and to perform preliminary calculations based on the input information. The task acquisition unit is used to acquire calculation results and simulation task record table, and to determine the process, activities, job objects, and resources required for each specific task in the process simulation model. The execution unit is used to obtain the start time of each specific task and execute the tasks in the order of their start times. The simulation calculation unit is used to acquire resource usage records. Based on the start time of each specific task, the task process, activities, resources required for the activities, and resource usage, it calculates the actual execution information of each specific task and records the simulation calculation results of task execution and resource usage. The optimization unit is used to optimize resources through a heuristic bidirectional simulation resource optimization method; after traversing and executing each specific task, the simulation ends and outputs simulation result information.

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