Space-time coordination based vertical and horizontal transportation mixed scheduling system and method
By constructing a set of historical and real-time collaborative performance data and dynamically adjusting task allocation weights, the problems of equipment resource conflicts and low scheduling efficiency in traditional scheduling methods are solved. This enables spatiotemporal collaborative scheduling of vertical and horizontal transportation equipment, thereby improving port operation efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG YIGANGTONG ELECTRONIC COMMERCE CO LTD
- Filing Date
- 2026-06-03
- Publication Date
- 2026-07-03
AI Technical Summary
Traditional hybrid scheduling methods for vertical and horizontal transportation suffer from problems such as low scheduling efficiency, frequent equipment resource conflicts, and lack of intelligent dynamic control and global collaborative scheduling capabilities when multiple devices are linked, dynamic operating conditions are managed, and spatiotemporal dimensions are coordinated.
By constructing a set of historical and real-time collaborative performance data, normalizing the time consumption of a single task by the equipment and weighting the queue length, calculating the load characteristic curve, and combining the rated operating capacity of the equipment with the real-time load status, the task allocation weight is dynamically adjusted to achieve the scheduling of vertical and horizontal transportation equipment in a time-space collaborative manner.
It has achieved time-series matching of vertical and horizontal transportation equipment and adaptive equipment load optimization, thereby improving port cargo turnover efficiency and overall throughput.
Smart Images
Figure CN122334895A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data analysis technology, specifically to a hybrid scheduling system and method for vertical and horizontal transportation based on spatiotemporal coordination. Background Technology
[0002] With the rapid advancement of smart port and automated terminal construction, the collaborative operation of vertical transportation equipment and horizontal transportation equipment has become a core link in port and shipping container transshipment. The scheduling efficiency of transportation equipment such as trucks and quay cranes directly determines the port's cargo turnover timeliness and overall throughput.
[0003] However, traditional hybrid scheduling methods for vertical and horizontal transportation often face the following problems when dealing with multi-equipment linkage, dynamic operating condition management, and spatiotemporal coordination: First, scheduling efficiency is low, and equipment resource conflicts occur frequently. Ports have a large number of trucks, gantry cranes, hoists, and other equipment, and complex operating scenarios. Traditional scheduling often adopts a static task allocation model, without considering time and space dimensions for overall planning, easily leading to problems such as equipment waiting idly, path congestion, and delays in the connection between vertical lifting and horizontal transfer. Second, scheduling lacks intelligent dynamic control methods, making it difficult to adapt to changing operating conditions. Traditional scheduling cannot achieve time-series matching of vertical and horizontal equipment, easily causing operational process breaks. Furthermore, it lacks global collaborative scheduling capabilities, failing to dynamically allocate task weights based on factors such as equipment rated operating capacity, real-time load, and task priority, thus failing to achieve optimal global operation matching for multiple devices. Summary of the Invention
[0004] The purpose of this invention is to provide a hybrid scheduling system and method for vertical and horizontal transportation based on spatiotemporal coordination, so as to solve the problems raised in the prior art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination, the method comprising the following steps: Obtain information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment; Based on historical operation logs, the operation parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; at the same time, real-time status data is collected to construct a real-time collaborative efficiency set. The time taken for a single task on each device is normalized by minimum-maximum, and then weighted and merged with the normalized queue length to construct its historical load characteristic curve. Get the current task allocation request volume, match the composite load value with the same request volume in the historical load characteristic curve, calculate the average value as the standard operating load and determine the fluctuation range; calculate the theoretical load value by combining the total number of similar devices before and after expansion; calculate the current actual load value; compare the actual and theoretical load values, and adjust the task allocation weight when it exceeds the fluctuation range; The total number of pairing tasks for vertical and planar devices and the number of successful spatiotemporal collaborations are counted. The hit rate is calculated, and task weights are assigned based on the hit rate.
[0006] The process of acquiring information on newly added transportation equipment and determining its initial task allocation weight based on its rated operating capacity includes the following steps: Obtain relevant information about newly added transportation equipment, including the unique transportation equipment identifier, transportation equipment type code, the work area group to which the transportation equipment belongs, the spatial positioning reference of the transportation equipment, the maximum working radius of the transportation equipment, the historical average work cycle time, the default driving speed curve, and the minimum safe time interval between the transportation equipment and other transportation equipment types. The initial task allocation weight w for newly added transportation equipment is configured based on the rated operating capacity of the existing transportation equipment. j The definition is as follows: w j =c j / c j '; where c j c represents the rated capacity index of the newly added transportation equipment of category j. j ' represents the reference capacity value of the newly added transportation equipment of the jth category. For container trucks, the rated capacity index can be selected as the rated load, and the reference capacity value can be selected as the average value of the rated capacity index of the same type of equipment. For quay cranes, the rated capacity index can be selected as the rated number of lifting operations. For yard cranes, the rated capacity index can be selected as the rated number of stacking operations.
[0007] Based on historical operation logs, operational parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; simultaneously, real-time status data is collected to construct a real-time collaborative efficiency set. Specific steps include: Based on the timestamp of this scheduling adjustment and the unique identifier of all transportation equipment, historical operation log data within a preset time window is obtained according to the unique identifier of each transportation equipment. Among them, all transportation equipment includes newly added transportation equipment and existing transportation equipment. The preset time window can be set to 30 minutes; The log timestamps of each historical operation log entry are verified, and log entries whose timestamps are earlier than the trigger timestamp of this scheduling adjustment are selected to form valid historical operation log data. The valid historical operation log data is structured and parsed to extract the parameters recorded in the valid historical operation log data, including the single operation time of the vertical transportation equipment, the idle waiting time of the vertical transportation equipment, the number of operation conflicts of the vertical transportation equipment, the single transportation time of the horizontal transportation equipment, the queuing waiting time of the horizontal transportation equipment, and the empty mileage of the horizontal transportation equipment. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted parameters are used as the key to construct a historical collaborative efficiency set. Collect real-time status data of all transportation equipment at the current moment, including the current work queue length of vertical transportation equipment, the real-time idle status of vertical transportation equipment, the current position coordinates of horizontal transportation equipment, the real-time speed of horizontal transportation equipment, and the current task status of horizontal transportation equipment. The current task status includes idle, running, and fault. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted real-time status data is used as the key to construct a real-time collaborative efficiency set.
[0008] The time taken for a single task on each device is normalized using a minimum-maximum normalization method, and then weighted and fused with the normalized queue length to construct its historical load characteristic curve. Specific steps include: Extract the single task time data of each transportation equipment from the historical collaborative efficiency set. For vertical transportation equipment, extract the single operation time from the start of hoisting to the end; for horizontal transportation equipment, extract the single transportation time from the start of the task to the completion. Using the unique identifier of each transportation device as the lookup index, the time consumption data of each device is sorted in timestamp order. The time consumption sequence of each device is then independently subjected to min-max normalization, ensuring that the normalized operation time value falls within the [0,1] interval. The calculation formula is as follows: t i =(tt i,min ) / (t i,max -t i,min ); where t i Let represent the dimensionless value of the single operation time of the i-th transport equipment in a specific task after min-max normalization, and t represent the actual time of this task. For vertical transport equipment, it refers to the cycle time of a single hoisting operation; for horizontal transport equipment, it refers to the travel time of a single transport task. i,min Let t represent the fastest time for the i-th transport device to complete the task under optimal operating conditions. i,max This represents the slowest time for the i-th transport device to complete the task under extreme congestion or malfunction conditions; The load calculation weight parameters are preset based on human experience. The load calculation weight parameters include the historical operation time weight coefficient of vertical transportation equipment, the current queue length weight coefficient of vertical transportation equipment, the historical transportation time weight coefficient of horizontal transportation equipment, and the current queue number of tasks weight coefficient of horizontal transportation equipment. For each vertical transport device, its normalized historical operation time and normalized queue length are weighted and fused to obtain a composite load value. For each horizontal transport device, its normalized historical transport time and normalized queued task number are weighted and fused to obtain a composite load value. With the task allocation frequency as the horizontal axis and the composite load value as the vertical axis, an independent historical load characteristic curve is constructed for each transport device. The normalized queue length is calculated by dividing the actual number of queued tasks at the time of the task occurrence by the preset maximum acceptable queue length; the normalized queued task number is calculated by dividing the actual number of waiting tasks at the time of the task occurrence by the preset maximum acceptable queued task number.
[0009] The process involves: obtaining the current task allocation request volume; matching the composite load value with the same request volume in the historical load characteristic curve; calculating the average value as the standard operating load and determining the fluctuation range; calculating the theoretical load value by combining the total number of similar devices before and after capacity expansion; calculating the current actual load value; comparing the actual and theoretical load values; and adjusting the task allocation weight if the load exceeds the fluctuation range. Specific steps include: Obtain the current task allocation request volume of each transportation device in the real-time collaborative efficiency set, match all historical composite load values corresponding to the same request volume in the historical load characteristic curve of the corresponding transportation device according to the current request volume, calculate the mean of the remaining historical load values as the standard operating load, and calculate the standard deviation to determine the fluctuation range using the three sigma principle. Based on the total number of similar transportation equipment before and after this scheduling adjustment, calculate the theoretical load value L0 for each transportation equipment. (i) The definition is as follows: L0 (i) =L1 (i) ×Nb / Na; where L1 (i) Nb represents the standard operating load of the i-th transport equipment, Nb represents the total number of this type of transport equipment before the expansion, and Na represents the total number of transport equipment after the expansion. The current task allocation request quantity can be selected as the number of loading / unloading tasks or transportation tasks to be allocated; Based on the real-time collaborative efficiency set, the current actual load value of each transportation device is calculated synchronously, as defined below: For vertical transportation equipment, the normalized value of its most recent historical task time is weighted and fused with the normalized value of the current queue length; for horizontal transportation equipment, the normalized value of its most recent historical transportation time is weighted and fused with the normalized value of the current number of queued tasks. The normalized value of the current queue length is calculated by dividing the current number of queued tasks by the maximum acceptable queue length, and the normalized value of the current number of queued tasks is calculated by dividing the current number of pending tasks by the maximum acceptable number of queued tasks. By comparing the current actual load value with the theoretical load value, the task allocation weights are dynamically configured for the first time. The specific steps are as follows: When the actual load value is higher than the theoretical load value and exceeds the fluctuation range, the task allocation weight of the transportation equipment will be reduced by 10% based on its unique identifier. When the actual load value is lower than the theoretical load value and exceeds the fluctuation range, the task allocation weight will be increased by 10% of the current weight. When the actual load value is within the theoretical load value and fluctuation range, the current weight remains unchanged, and the first dynamic configuration is completed.
[0010] The total number of pairing tasks and spatiotemporal collaboration successes for vertical and planar devices are counted, the hit rate is calculated, and task weights are assigned based on the hit rate. Specific steps include: Analyze whether the transportation equipment is an independent operating transportation equipment. For independent operating transportation equipment, keep its weight unchanged after the first dynamic configuration, mark it as an object not to be adjusted, and determine whether the conditions for continued monitoring are met. If no stop instruction is received, repeat the steps of historical log acquisition, real-time data collection, first dynamic configuration, and second dynamic configuration. If a stop instruction is received, end the monitoring process. For non-independent operating transportation equipment, mark it as an object for secondary weight adjustment. Obtain the operation log of the weighted secondary adjustment object within the time window after the first dynamic configuration, and extract the parameters recorded in the log, including the total number of pairing tasks between vertical transportation equipment and horizontal transportation equipment, and the number of spatiotemporal collaboration hits. The spatiotemporal collaboration hit is defined as when the horizontal transportation equipment arrives at the operation area of the vertical transportation equipment, the vertical transportation equipment is already in an idle and ready state, the spatial distance between the two is less than the safe spatial distance threshold, and the waiting time does not exceed the preset buffer time. The safe spatial distance threshold can be selected as 5 cm. The waiting time is defined as the time interval from the completion of the previous task to the start of service for this task after the horizontal transportation equipment arrives at the operation point. The preset buffer time can be selected as 10 seconds. Based on the ratio of the number of hits to the total number of missions, the spatiotemporal coordination hit rate of each transportation equipment pair is calculated. Synchronize and associate the task allocation weights of each transportation device after the initial dynamic configuration; For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate.
[0011] For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate. The specific steps include: When the time-space coordination hit rate is higher than the associated baseline hit rate during the first dynamic configuration, its task allocation weight is increased by 10% of the current weight. The associated baseline hit rate during the first dynamic configuration is defined as the historical average hit rate of the transportation equipment pair. When the spatiotemporal coordination hit rate is lower than the associated baseline hit rate, its task allocation weight will be reduced by 10% of the current weight; When the spatiotemporal collaborative hit rate is consistent with the associated baseline hit rate, the weights after the first dynamic configuration remain unchanged; After completing the second dynamic configuration, continuously monitor the real-time status data of all transportation equipment and determine whether the conditions for continued monitoring are met: if no stop instruction is received, repeat the steps of historical log acquisition, real-time data collection, first dynamic configuration, and second dynamic configuration; if a stop instruction is received, end the monitoring process.
[0012] A hybrid scheduling system for vertical and horizontal transportation based on spatiotemporal coordination, comprising: Equipment information acquisition module, performance set construction module, load characteristic analysis module, dynamic weight scheduling module; The output of the device information acquisition module is connected to the input of the performance set construction module; the output of the performance set construction module is connected to the input of the load characteristic analysis module; and the output of the load characteristic analysis module is connected to the input of the dynamic weight scheduling module.
[0013] The equipment information acquisition module is used to acquire information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment. The performance set construction module includes a historical log extraction unit, a real-time status acquisition unit, and a performance data collection unit. The historical log extraction unit is used to extract the historical operation logs of the equipment within a preset window. The real-time status acquisition unit is used to collect the real-time location, queue, and idle status of the equipment. The performance data collection unit is used to construct two types of collaborative performance sets: historical and real-time.
[0014] The load characteristic analysis module includes a time consumption normalization unit, a queue data fusion unit, and a load curve construction unit; the time consumption normalization unit is used to normalize the time consumption data of a single task of the device; the queue data fusion unit is used to weight and fuse the time consumption and queue length to generate a composite load; the load curve construction unit is used to generate a historical load characteristic curve of a single device; The dynamic weight scheduling module includes an initial weight configuration unit, a load weight adjustment unit, and a collaborative weight optimization unit. The initial weight configuration unit is used to set the initial task weight of the equipment according to the rated capacity. The load weight adjustment unit is used to dynamically adjust the weight by comparing the actual and theoretical loads. The collaborative weight optimization unit is used to perform secondary optimization of the weight based on the spatiotemporal collaborative hit rate.
[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. By coordinating the operation sequence of vertical and horizontal transportation equipment in a spatiotemporal dimension, and combining the rated operating capacity of the equipment and the real-time load status to identify spatiotemporal operation conflicts of multiple equipment, this invention can achieve time sequence matching of vertical and horizontal transportation equipment, unlike the static scheduling mode of the existing technology. 2. This invention introduces a dynamic task weight allocation mechanism, which configures the initial weight based on the rated operating capacity of the equipment, dynamically adjusts the scheduling weight in combination with real-time load characteristics, and further optimizes the allocation logic based on spatiotemporal coordination. Unlike the fixed task allocation method of the existing technology, this invention can adapt to the operating load of the equipment. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to the present invention. Detailed Implementation
[0017] 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 embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] like Figure 1 As shown, this invention provides a technical solution: a hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination. This method includes the following steps: Obtain information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment; Based on historical operation logs, the operation parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; at the same time, real-time status data is collected to construct a real-time collaborative efficiency set. The time taken for a single task on each device is normalized by minimum-maximum, and then weighted and merged with the normalized queue length to construct its historical load characteristic curve. Get the current task allocation request volume, match the composite load value with the same request volume in the historical load characteristic curve, calculate the average value as the standard operating load and determine the fluctuation range; calculate the theoretical load value by combining the total number of similar devices before and after expansion; calculate the current actual load value; compare the actual and theoretical load values, and adjust the task allocation weight when it exceeds the fluctuation range; The total number of pairing tasks for vertical and planar devices and the number of successful spatiotemporal collaborations are counted. The hit rate is calculated, and task weights are assigned based on the hit rate.
[0019] The process of acquiring information on newly added transportation equipment and determining its initial task allocation weight based on its rated operating capacity includes the following steps: Obtain relevant information about newly added transportation equipment, including the unique transportation equipment identifier, transportation equipment type code, the work area group to which the transportation equipment belongs, the spatial positioning reference of the transportation equipment, the maximum working radius of the transportation equipment, the historical average work cycle time, the default driving speed curve, and the minimum safe time interval between the transportation equipment and other transportation equipment types. The initial task allocation weight w for newly added transportation equipment is configured based on the rated operating capacity of the existing transportation equipment. j The definition is as follows: w j =c j / c j '; where c j c represents the rated capacity index of the newly added transportation equipment of category j. j ' represents the reference capacity value of the newly added transportation equipment of the jth category. For container trucks, the rated capacity index can be selected as the rated load, and the reference capacity value can be selected as the average value of the rated capacity index of the same type of equipment. For quay cranes, the rated capacity index can be selected as the rated number of lifting operations. For yard cranes, the rated capacity index can be selected as the rated number of stacking operations.
[0020] Based on historical operation logs, operational parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; simultaneously, real-time status data is collected to construct a real-time collaborative efficiency set. Specific steps include: Based on the timestamp of this scheduling adjustment and the unique identifier of all transportation equipment, historical operation log data within a preset time window is obtained according to the unique identifier of each transportation equipment. Among them, all transportation equipment includes newly added transportation equipment and existing transportation equipment. The preset time window can be set to 30 minutes; The log timestamps of each historical operation log entry are verified, and log entries whose timestamps are earlier than the trigger timestamp of this scheduling adjustment are selected to form valid historical operation log data. The valid historical operation log data is structured and parsed to extract the parameters recorded in the valid historical operation log data, including the single operation time of the vertical transportation equipment, the idle waiting time of the vertical transportation equipment, the number of operation conflicts of the vertical transportation equipment, the single transportation time of the horizontal transportation equipment, the queuing waiting time of the horizontal transportation equipment, and the empty mileage of the horizontal transportation equipment. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted parameters are used as the key to construct a historical collaborative efficiency set. Collect real-time status data of all transportation equipment at the current moment, including the current work queue length of vertical transportation equipment, the real-time idle status of vertical transportation equipment, the current position coordinates of horizontal transportation equipment, the real-time speed of horizontal transportation equipment, and the current task status of horizontal transportation equipment. The current task status includes idle, running, and fault. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted real-time status data is used as the key to construct a real-time collaborative efficiency set.
[0021] The time taken for a single task on each device is normalized using a minimum-maximum normalization method, and then weighted and fused with the normalized queue length to construct its historical load characteristic curve. Specific steps include: Extract the single task time data of each transportation equipment from the historical collaborative efficiency set. For vertical transportation equipment, extract the single operation time from the start of hoisting to the end; for horizontal transportation equipment, extract the single transportation time from the start of the task to the completion. Using the unique identifier of each transportation device as the lookup index, the time consumption data of each device is sorted in timestamp order. The time consumption sequence of each device is then independently subjected to min-max normalization, ensuring that the normalized operation time value falls within the [0,1] interval. The calculation formula is as follows: t i =(tt i,min ) / (t i,max -t i,min ); where t i Let represent the dimensionless value of the single operation time of the i-th transport equipment in a specific task after min-max normalization, and t represent the actual time of this task. For vertical transport equipment, it refers to the cycle time of a single hoisting operation; for horizontal transport equipment, it refers to the travel time of a single transport task. i,min Let t represent the fastest time for the i-th transport device to complete the task under optimal operating conditions. i,max This represents the slowest time for the i-th transport device to complete the task under extreme congestion or malfunction conditions; The load calculation weight parameters are preset based on human experience. The load calculation weight parameters include the historical operation time weight coefficient of vertical transportation equipment, the current queue length weight coefficient of vertical transportation equipment, the historical transportation time weight coefficient of horizontal transportation equipment, and the current queue number of tasks weight coefficient of horizontal transportation equipment. For each vertical transport device, its normalized historical operation time and normalized queue length are weighted and fused to obtain a composite load value. For each horizontal transport device, its normalized historical transport time and normalized queued task number are weighted and fused to obtain a composite load value. With the task allocation frequency as the horizontal axis and the composite load value as the vertical axis, an independent historical load characteristic curve is constructed for each transport device. The normalized queue length is calculated by dividing the actual number of queued tasks at the time of the task occurrence by the preset maximum acceptable queue length; the normalized queued task number is calculated by dividing the actual number of waiting tasks at the time of the task occurrence by the preset maximum acceptable queued task number.
[0022] The process involves: obtaining the current task allocation request volume; matching the composite load value with the same request volume in the historical load characteristic curve; calculating the average value as the standard operating load and determining the fluctuation range; calculating the theoretical load value by combining the total number of similar devices before and after capacity expansion; calculating the current actual load value; comparing the actual and theoretical load values; and adjusting the task allocation weight if the load exceeds the fluctuation range. Specific steps include: Obtain the current task allocation request volume of each transportation device in the real-time collaborative efficiency set, match all historical composite load values corresponding to the same request volume in the historical load characteristic curve of the corresponding transportation device according to the current request volume, calculate the mean of the remaining historical load values as the standard operating load, and calculate the standard deviation to determine the fluctuation range using the three sigma principle. Based on the total number of similar transportation equipment before and after this scheduling adjustment, calculate the theoretical load value L0 for each transportation equipment. (i) The definition is as follows: L0 (i) =L1 (i) ×Nb / Na; where L1 (i) Nb represents the standard operating load of the i-th transport equipment, Nb represents the total number of this type of transport equipment before the expansion, and Na represents the total number of transport equipment after the expansion. The current task allocation request quantity can be selected as the number of loading / unloading tasks or transportation tasks to be allocated; Based on the real-time collaborative efficiency set, the current actual load value of each transportation device is calculated synchronously, as defined below: For vertical transportation equipment, the normalized value of its most recent historical task time is weighted and fused with the normalized value of the current queue length; for horizontal transportation equipment, the normalized value of its most recent historical transportation time is weighted and fused with the normalized value of the current number of queued tasks. The normalized value of the current queue length is calculated by dividing the current number of queued tasks by the maximum acceptable queue length, and the normalized value of the current number of queued tasks is calculated by dividing the current number of pending tasks by the maximum acceptable number of queued tasks. By comparing the current actual load value with the theoretical load value, the task allocation weights are dynamically configured for the first time. The specific steps are as follows: When the actual load value is higher than the theoretical load value and exceeds the fluctuation range, the task allocation weight of the transportation equipment will be reduced by 10% based on its unique identifier. When the actual load value is lower than the theoretical load value and exceeds the fluctuation range, the task allocation weight will be increased by 10% of the current weight. When the actual load value is within the theoretical load value and fluctuation range, the current weight remains unchanged, and the first dynamic configuration is completed.
[0023] The total number of pairing tasks and spatiotemporal collaboration successes for vertical and planar devices are counted, the hit rate is calculated, and task weights are assigned based on the hit rate. Specific steps include: Analyze whether the transportation equipment is an independent operation transportation equipment. For independent operation transportation equipment, keep its weight unchanged after the first dynamic configuration and mark it as an object not to be adjusted; for non-independent operation transportation equipment, mark it as an object for secondary weight adjustment. Obtain the operation log of the weighted secondary adjustment object within the time window after the first dynamic configuration, and extract the parameters recorded in the log, including the total number of pairing tasks between vertical transportation equipment and horizontal transportation equipment, and the number of spatiotemporal collaboration hits. The spatiotemporal collaboration hit is defined as when the horizontal transportation equipment arrives at the operation area of the vertical transportation equipment, the vertical transportation equipment is already in an idle and ready state, the spatial distance between the two is less than the safe spatial distance threshold, and the waiting time does not exceed the preset buffer time. The safe spatial distance threshold can be selected as 5 cm. The waiting time is defined as the time interval from the completion of the previous task to the start of service for this task after the horizontal transportation equipment arrives at the operation point. The preset buffer time can be selected as 10 seconds. Based on the ratio of the number of hits to the total number of missions, the spatiotemporal coordination hit rate of each transportation equipment pair is calculated. Synchronize and associate the task allocation weights of each transportation device after the initial dynamic configuration; For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate.
[0024] For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate. The specific steps include: When the time-space coordination hit rate is higher than the associated baseline hit rate during the first dynamic configuration, its task allocation weight is increased by 10% of the current weight. The associated baseline hit rate during the first dynamic configuration is defined as the historical average hit rate of the transportation equipment pair. When the spatiotemporal coordination hit rate is lower than the associated baseline hit rate, its task allocation weight will be reduced by 10% of the current weight; When the spatiotemporal collaborative hit rate is consistent with the associated baseline hit rate, the weights after the first dynamic configuration remain unchanged; After completing the second dynamic configuration, we continuously monitor the real-time status data of all transportation equipment.
[0025] In Example 1: the basic attribute information of the existing transportation equipment and the newly put into use in the site is obtained, the functional types of different equipment are sorted out, the rated operating capacity of each type of equipment is analyzed, and the operating characteristics of vertical hoisting equipment and planar transport equipment are distinguished. Collect historical operation information of various transportation equipment, and collect real-time information on equipment operation location and idle status, taking into account both the time dimension of operation sequence and the spatial dimension of operation area to construct a set of equipment operation efficiency. By analyzing the operating time of various transportation equipment and combining it with the cargo transfer volume in the yard, the actual operating load of the equipment is calculated, the load change characteristics are analyzed, and the operating load status of the equipment is identified. Equipment task scheduling is completed based on spatiotemporal collaborative logic. First, the initial task allocation weights are configured for various types of equipment according to their rated operating capacity, and then the weight allocation ratios are dynamically adjusted in combination with the real-time load status of the equipment.
[0026] A hybrid scheduling system for vertical and horizontal transportation based on spatiotemporal coordination, comprising: Equipment information acquisition module, performance set construction module, load characteristic analysis module, dynamic weight scheduling module; The output of the device information acquisition module is connected to the input of the performance set construction module; the output of the performance set construction module is connected to the input of the load characteristic analysis module; and the output of the load characteristic analysis module is connected to the input of the dynamic weight scheduling module.
[0027] The equipment information acquisition module is used to acquire information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment. The performance set construction module includes a historical log extraction unit, a real-time status acquisition unit, and a performance data collection unit. The historical log extraction unit is used to extract the historical operation logs of the equipment within a preset window. The real-time status acquisition unit is used to collect the real-time location, queue, and idle status of the equipment. The performance data collection unit is used to construct two types of collaborative performance sets: historical and real-time.
[0028] The load characteristic analysis module includes a time consumption normalization unit, a queue data fusion unit, and a load curve construction unit; the time consumption normalization unit is used to normalize the time consumption data of a single task of the device; the queue data fusion unit is used to weight and fuse the time consumption and queue length to generate a composite load; the load curve construction unit is used to generate a historical load characteristic curve of a single device; The dynamic weight scheduling module includes an initial weight configuration unit, a load weight adjustment unit, and a collaborative weight optimization unit. The initial weight configuration unit is used to set the initial task weight of the equipment according to the rated capacity. The load weight adjustment unit is used to dynamically adjust the weight by comparing the actual and theoretical loads. The collaborative weight optimization unit is used to perform secondary optimization of the weight based on the spatiotemporal collaborative hit rate.
[0029] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
Claims
1. A hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination, characterized in that: The method includes the following steps: Obtain information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment; Based on historical operation logs, the operation parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; at the same time, real-time status data is collected to construct a real-time collaborative efficiency set. The single task time of each device is normalized and then weighted and merged with the normalized queue length to construct its historical load characteristic curve. Get the current task allocation request volume, match the composite load value with the same request volume in the historical load characteristic curve, calculate the average value as the standard operating load and determine the fluctuation range; calculate the theoretical load value by combining the total number of similar devices before and after expansion; calculate the current actual load value; compare the actual and theoretical load values, and adjust the task allocation weight when it exceeds the fluctuation range; The total number of pairing tasks for vertical and planar devices and the number of successful spatiotemporal collaborations are counted. The hit rate is calculated, and task weights are assigned based on the hit rate.
2. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 1, characterized in that: The process of acquiring information on newly added transportation equipment and determining its initial task allocation weight based on its rated operating capacity includes the following steps: Obtain relevant information about newly added transportation equipment, including the unique transportation equipment identifier, transportation equipment type code, the work area group to which the transportation equipment belongs, the spatial positioning reference of the transportation equipment, the maximum working radius of the transportation equipment, the historical average work cycle time, the default driving speed curve, and the minimum safe time interval between the transportation equipment and other transportation equipment types. The initial task allocation weight w of the newly added transportation equipment is configured based on the rated operation capacity of the transportation equipment j , and is defined as shown below: j w = c j / c j '; wherein c j represents the rated capacity index of the jth newly added transportation equipment, and c j ' represents the reference capacity value of the jth newly added transportation equipment.
3. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 2, characterized in that: Based on historical operation logs, the operation parameters of vertical and horizontal equipment are extracted to construct a historical collaborative efficiency set; Simultaneously, real-time status data is collected to construct a real-time collaborative performance set. Specific steps include: Based on the timestamp of this scheduling adjustment and the unique identifier of all transportation equipment, historical operation log data within a preset time window is obtained according to the unique identifier of each transportation equipment. Among them, all transportation equipment includes newly added transportation equipment and existing transportation equipment. The log timestamps of each historical operation log entry are verified, and log entries whose timestamps are earlier than the trigger timestamp of this scheduling adjustment are selected to form valid historical operation log data. The valid historical operation log data is structured and parsed to extract the parameters recorded in the valid historical operation log data, including the single operation time of the vertical transportation equipment, the idle waiting time of the vertical transportation equipment, the number of operation conflicts of the vertical transportation equipment, the single transportation time of the horizontal transportation equipment, the queuing waiting time of the horizontal transportation equipment, and the empty mileage of the horizontal transportation equipment. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted parameters are used as the key to construct a historical collaborative efficiency set. Collect real-time status data of all transportation equipment at the current moment, including the current work queue length of vertical transportation equipment, the real-time idle status of vertical transportation equipment, the current position coordinates of horizontal transportation equipment, the real-time speed of horizontal transportation equipment, and the current task status of horizontal transportation equipment. The current task status includes idle, running, and fault. Based on the unique identifier of the transportation equipment, the equipment is classified and grouped, and the extracted real-time status data is used as the key to construct a real-time collaborative efficiency set.
4. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 3, characterized in that: The time taken for a single task on each device is normalized using a minimum-maximum normalization method, and then weighted and fused with the normalized queue length to construct its historical load characteristic curve. Specific steps include: Extract the single task time data of each transportation equipment from the historical collaborative efficiency set. For vertical transportation equipment, extract the single operation time from the start of hoisting to the end; for horizontal transportation equipment, extract the single transportation time from the start of the task to the completion. Using the unique identifier of each transportation device as the lookup index, the time consumption data of each device is sorted in timestamp order. The time consumption sequence of each device is then independently subjected to min-max normalization, ensuring that the normalized operation time value falls within the [0,1] interval. The calculation formula is as follows: t i =(tt i,min ) / (t i,max -t i,min ); where t i Let represent the dimensionless value of the single operation time of the i-th transport equipment in a specific task after min-max normalization, and t represent the actual time of this task. For vertical transport equipment, it refers to the cycle time of a single hoisting operation; for horizontal transport equipment, it refers to the travel time of a single transport task. i,min Let t represent the fastest time for the i-th transport device to complete the task under optimal operating conditions. i,max This represents the slowest time for the i-th transport device to complete the task under extreme congestion or malfunction conditions; The load calculation weight parameters are preset based on human experience. The load calculation weight parameters include the historical operation time weight coefficient of vertical transportation equipment, the current queue length weight coefficient of vertical transportation equipment, the historical transportation time weight coefficient of horizontal transportation equipment, and the current queue number of tasks weight coefficient of horizontal transportation equipment. For each vertical transport device, its normalized historical operation time and normalized queue length are weighted and fused to obtain a composite load value; for each horizontal transport device, its normalized historical transport time and normalized queue number are weighted and fused to obtain a composite load value. The number of task allocations is selected as the horizontal axis and the composite load value is selected as the vertical axis to construct an independent historical load characteristic curve for each transport device.
5. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 4, characterized in that: Obtain the current task allocation request volume, match the composite load value with the same request volume in the historical load characteristic curve, calculate the average value as the standard operating load and determine the fluctuation range; combine the total number of the same type of equipment before and after the expansion to calculate the theoretical load value; Calculate the current actual load value; When comparing actual and theoretical load values, and if the load exceeds the fluctuation range, the task allocation weights are adjusted. Specific steps include: Obtain the current task allocation request volume of each transportation device in the real-time collaborative efficiency set, match all historical composite load values corresponding to the same request volume in the historical load characteristic curve of the corresponding transportation device according to the current request volume, calculate the mean of the remaining historical load values as the standard operating load, and calculate the standard deviation to determine the fluctuation range using the three sigma principle. Based on the total number of similar transportation equipment before and after this scheduling adjustment, calculate the theoretical load value L0 for each transportation equipment. (i) The definition is as follows: L0 (i) =L1 (i) ×Nb / Na; where L1 (i) Nb represents the standard operating load of the i-th transport equipment, Nb represents the total number of this type of transport equipment before the expansion, and Na represents the total number of transport equipment after the expansion. Based on the real-time collaborative efficiency set, the current actual load value of each transportation device is calculated synchronously, as defined below: For vertical transportation equipment, the normalized value of its most recent historical task time is weighted and fused with the normalized value of the current queue length; for horizontal transportation equipment, the normalized value of its most recent historical transportation time is weighted and fused with the normalized value of the current queue number of tasks. By comparing the current actual load value with the theoretical load value, the task allocation weights are dynamically configured for the first time. The specific steps are as follows: When the actual load value is higher than the theoretical load value and exceeds the fluctuation range, the task allocation weight of the transportation equipment is reduced according to its unique identifier; when the actual load value is lower than the theoretical load value and exceeds the fluctuation range, the task allocation weight is increased. When the actual load value is within the theoretical load value and fluctuation range, the current weight remains unchanged, and the first dynamic configuration is completed.
6. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 5, characterized in that: The total number of pairing tasks and spatiotemporal collaboration successes for vertical and planar devices are counted, the hit rate is calculated, and task weights are assigned based on the hit rate. Specific steps include: Analyze whether the transportation equipment is an independent operation transportation equipment. For independent operation transportation equipment, keep its weight unchanged after the first dynamic configuration and mark it as an object not to be adjusted; for non-independent operation transportation equipment, mark it as an object for secondary weight adjustment. Obtain the operation log of the weighted secondary adjustment object within the time window after the first dynamic configuration, and extract the parameters recorded in the log, including the total number of pairing tasks between vertical transportation equipment and horizontal transportation equipment, and the number of spatiotemporal coordination hits. The spatiotemporal coordination hit is defined as when the horizontal transportation equipment arrives at the operation area of the vertical transportation equipment, the vertical transportation equipment is already in an idle and ready state, the spatial distance between the two is less than the safe spatial distance threshold, and the waiting time does not exceed the preset buffer time. Based on the ratio of the number of hits to the total number of missions, the spatiotemporal coordination hit rate of each transportation equipment pair is calculated. Synchronize and associate the task allocation weights of each transportation device after the initial dynamic configuration; For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate.
7. The hybrid scheduling method for vertical and horizontal transportation based on spatiotemporal coordination according to claim 6, characterized in that: For objects subject to secondary weight adjustment, the task allocation weights are reconfigured based on their spatiotemporal collaborative hit rate. The specific steps include: When the time-space coordination hit rate is higher than the associated baseline hit rate during the first dynamic configuration, its task allocation weight is increased. The associated baseline hit rate during the first dynamic configuration is defined as the historical average hit rate of the transportation equipment pair. When the hit rate of spatiotemporal coordination is lower than the baseline hit rate, the task allocation weight is reduced. When the spatiotemporal collaborative hit rate is consistent with the associated baseline hit rate, the weights after the first dynamic configuration remain unchanged; After completing the second dynamic configuration, we continuously monitor the real-time status data of all transportation equipment.
8. A spatiotemporal collaborative vertical and horizontal transportation hybrid scheduling system, applied to the spatiotemporal collaborative vertical and horizontal transportation hybrid scheduling method according to any one of claims 1-7, characterized in that: The system includes: Equipment information acquisition module, performance set construction module, load characteristic analysis module, dynamic weight scheduling module; The output of the device information acquisition module is connected to the input of the performance set construction module; the output of the performance set construction module is connected to the input of the load characteristic analysis module; and the output of the load characteristic analysis module is connected to the input of the dynamic weight scheduling module.
9. The spatiotemporal collaborative vertical and planar transportation hybrid scheduling system according to claim 8, characterized in that: The equipment information acquisition module is used to acquire information on newly added transportation equipment and determine its initial task allocation weight based on the rated operating capacity of the transportation equipment. The performance set construction module includes a historical log extraction unit, a real-time status acquisition unit, and a performance data collection unit. The historical log extraction unit is used to extract the historical operation logs of the equipment within a preset window. The real-time status acquisition unit is used to collect the real-time location, queue, and idle status of the equipment. The performance data collection unit is used to construct two types of collaborative performance sets: historical and real-time.
10. The spatiotemporal collaborative vertical and planar transportation hybrid scheduling system according to claim 9, characterized in that: The load characteristic analysis module includes a time consumption normalization unit, a queue data fusion unit, and a load curve construction unit; the time consumption normalization unit is used to normalize the time consumption data of a single task of the device; the queue data fusion unit is used to weight and fuse the time consumption and queue length to generate a composite load; the load curve construction unit is used to generate a historical load characteristic curve of a single device; The dynamic weight scheduling module includes an initial weight configuration unit, a load weight adjustment unit, and a collaborative weight optimization unit. The initial weight configuration unit is used to set the initial task weight of the equipment according to the rated capacity. The load weight adjustment unit is used to dynamically adjust the weight by comparing the actual and theoretical loads. The collaborative weight optimization unit is used to perform secondary optimization of the weight based on the spatiotemporal collaborative hit rate.