CN110322106B - Luggage taking-in and dispatching method for multiple destination and multiple transport means - Google Patents
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Abstract
The invention provides a baggage picking and dispatching method related to a plurality of transportation tools with a plurality of destinations. According to the invention, through the destination allocation scheduling step and the destination access scheduling step, when a plurality of destinations are involved and a plurality of transportation means are needed to finish baggage picking and delivering, a place access sequence which meets the requirements of all orders as much as possible is planned for all baggage picking and delivering vehicles according to the time and place requirements of picking and delivering all baggage orders, the distance is short, the time is short, the baggage picking and delivering task is finished efficiently and time-saving, obvious improvement is brought for the travel convenience of people, and the blank in the prior art is filled.
Description
Technical Field
The present invention relates to a baggage handling and dispatching method, and more particularly to a baggage handling and dispatching method having a plurality of destinations and a plurality of transportation means.
Background
In travel, luggage has been a problem of headache, especially for travelers who drag their home with their mouth. Even today with very developed traffic, a distance still exists from airports, high-speed rail stations to hotels or at home, and especially in different places, public transportation means are often needed between a foothold point and the airports or the high-speed rail stations, if many pieces of luggage are carried, people are often embarrassed when the old and the children need to be cared for, and some travelers can only get out of high-price taxi taking or use hotel pickup service to avoid the disconcement of the journey. How to economically and rapidly solve the problem of headache luggage in the travel process has important significance for improving the travel experience of people and the travel quality.
At present, there is no method specifically for baggage picking and delivering, and in particular, an efficient baggage picking and delivering scheduling method which involves multiple destinations and is completed by multiple transportation means. The scheduling method not only can fill the blank in the field of baggage picking and scheduling, but also can improve the efficiency and the economy of a baggage picking and feeding system, and is very significant for improving the life quality of people.
Disclosure of Invention
The invention provides a baggage picking and dispatching method for a plurality of transportation tools with a plurality of destinations, aiming at the blank in the prior art. According to the invention, through the destination allocation scheduling step and the destination access scheduling step, when a plurality of destinations are involved and a plurality of transportation means are needed to finish baggage picking and delivering, a place access sequence which meets the requirements of all orders as much as possible is planned for all baggage picking and delivering vehicles according to the time and place requirements of picking and delivering all baggage orders, the distance is short, the time is short, the baggage picking and delivering task is finished efficiently, time and effort are saved, and obvious improvement is brought to the travel convenience of people.
The invention is realized by the following technical scheme:
a baggage picking and delivering dispatching method for multiple destination and multiple transportation means, wherein the baggage picking and delivering order submitted by the customer contains n baggage delivering destinations, and the baggage picking and delivering task is completed by m transportation means, comprising a destination distribution dispatching step and a destination access sequence dispatching step:
the destination allocation and scheduling step divides n destinations into m cluster sets through clusters, allocates the m cluster sets to m transport means, and each transport means corresponds to one cluster set, wherein the clusters enable the baggage taking place and the baggage delivering line Li Dedian to be the same in the baggage taking order received by the same transport means;
the target access sequence scheduling step allocates an access sequence for the target points in each cluster set, and the transport means where the cluster set is located accesses according to the allocation sequence to complete the baggage delivering task.
Further, the destination allocation scheduling step includes the steps of:
1.1, taking any m destinations, wherein the destinations comprise taking initial positions of baggage and baggage places or m transport means as cluster heads, and carrying out k-means clustering to obtain m clustering sets, wherein the using distance of the k-means clustering is space cost or time cost;
1.2, counting the repetition times of the baggage delivering places in each clustering set obtained in the step 1.1, and taking the place with the largest repetition times as a main destination of the clustering set;
when m is greater than or equal to n: if all n destinations become the main destination of at least one transport, destination allocation scheduling is completed, i.e. the order to which the destination belongs is allocated; the method comprises the steps of carrying out a first treatment on the surface of the If at least one destination does not become the main destination of one or more transportation means, counting the occurrence times of the destination in all cluster sets, and modifying the main destination of the cluster set with the largest occurrence times of the destination into the destination until all n destinations become the main destination of at least one transportation means;
when m < n: setting a destination k with the highest occurrence number in each cluster set as a main destination, wherein k is increased from 1 until all n destinations become the main destination of at least one transport means;
1.3, setting a non-primary destination in each cluster set as n_d, setting a cluster set with a primary destination as n_d as m_d, comparing the shortest distance between the non-primary destination in each cluster set and a cluster set with the primary destination as n_d, wherein the place comprises a baggage taking place and a baggage delivering place, and if the shortest distance is smaller than the average distance between the place and other places in the current cluster set, moving the place n_d from the current cluster set to the cluster set m_d; thus, the clustering is completed.
Further, the step 1.3 is as follows: comparing the time difference of the places between the non-primary destination n_d and the cluster set m_d with the primary destination n_d in each cluster set, specifically: setting the main destination of the clustering set J as d, for a place e (setting the destination corresponding to the place as q) with the destination not being d in the clustering set J, calculating the shortest distance from e to the place in the clustering set L with the main destination of q, and if the shortest distance is smaller than the average distance from e to the place in the clustering set J, moving e from the J set to the L; and repeating the step until the set of all orders is no longer changed and clustering is completed.
Further, the k-means clustering in the step 1.1 uses the space cost as the travel time between the destinations or the distance between the destinations; the destination includes baggage and travel Li Dedian, i.e., the location where each vehicle needs to pass; the driving time is estimated by the distance and road condition, and is directly read by an interface provided by navigation software at present, such as hundred degrees and high germany.
Further, the k-means cluster in step 1.1 uses a time difference between the time required for each baggage retrieval order to reach from the time cost.
Further, the destination access sequence scheduling step includes the steps of:
2.1, p destinations are arranged in each cluster set, the destinations comprise baggage taking places and delivery lines Li Dedian, travel time between the current place of the transport means and all the destinations without assigned access sequences is compared one by one, the destination with the shortest travel time is taken as the next station access place and assigned access sequence, and the place is taken as the current place of the transport means, and the steps are repeated until all the p destinations are assigned corresponding access sequences;
2.2 calculating the time tp of arrival of the transport at each destination according to the destination access sequence allocated in step 2.1, and calculating the difference td between tp and the time tr required by the order, the required time for the order being the required arrival time provided when the customer submitted the baggage retrieval information, i.e. generated the baggage retrieval order, and the total completion time Ta:the total completion time refers to the total time for the transport to sequentially access all destinations according to the assigned access order; the travel time is directly read by an interface provided by the navigation software as described above, such as hundred degrees, germany.
2.3 define the exclusion set Q and initialize to the null set:
for all destinations excluding the set Q, when td is less than or equal to 0, keeping the current access order unchanged; when td > 0: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, the forward movement is not effective, i.e. the forward movement is not performed, the original access sequence is kept, and then the next purpose is calculated by returning to the step 2.2;
if td is not reduced, the forward shift is not effective, i.e. the forward shift is not performed, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
2.4, comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order requirement time tr, if yes, finishing the steps, and finishing the distribution and scheduling of the destination access sequence; if not, the destination with the largest tr-tp value is rejected, and the step is carried out again until the estimated access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
Further, in said step 2.3: setting the baggage arrival time threshold to Td:
define the exclusion set Q and initialize to the null set: for all destinations excluding the set Q, when Td is less than or equal to Td, keeping the current access order unchanged; when Td > Td: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, the advance is not effective, i.e., no advance is performed;
if td is not reduced, the forward shift is not effective, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
2.4, comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order request time tr-Td, if yes, finishing the steps; if not, the destination with the largest tr-tp value is rejected and then is compared again until the expected access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
Further, the order merging step is advanced before the destination allocation scheduling step and the destination access scheduling step are performed: when the two orders are combined and the earlier time requirement is taken as the time requirement of the combined order when the orders with the same places and different required delivery times (if the time difference is not greater than T), wherein the time requirement is the time requirement submitted by a customer in the baggage taking and delivering order, the places are the same, the baggage taking place and the delivering Li Dedian are included, any place of one order is the same as any place of other orders, the T is a manual set value, and the T is determined according to the conditions of the specific order busy condition, road condition and the like on the same day.
The luggage taking and delivering scheduling method with a plurality of destinations and a plurality of transport means has the following technical effects: according to the invention, through the destination allocation scheduling step and the destination access scheduling step, when a plurality of destinations are involved and a plurality of transportation means are needed to finish baggage picking and delivering, a place access sequence which meets the requirements of all orders as much as possible is planned for all baggage picking and delivering vehicles according to the time and place requirements of picking and delivering all baggage orders, the distance is short, the time is short, the baggage picking and delivering task is finished efficiently and time-saving, obvious improvement is brought for the travel convenience of people, and the blank in the prior art is filled.
Detailed Description
In this section, the technical solution of the present invention will be further explained and explained. It should be noted that the present embodiment is only for explanation and illustration, and is not to be construed as limiting the invention, and the embodiments of the invention are not limited to one or more of the following.
Example 1
A baggage picking and delivering dispatching method for multiple destination and multiple transportation means, wherein the baggage picking and delivering order submitted by the customer contains n baggage delivering destinations, and the baggage picking and delivering task is completed by m transportation means, comprising a destination distribution dispatching step and a destination access sequence dispatching step:
the destination allocation and scheduling step divides n destinations into m cluster sets through clusters, allocates the m cluster sets to m transport means, and each transport means corresponds to one cluster set, wherein the clusters enable the baggage taking place and the baggage delivering line Li Dedian to be the same in the baggage taking order received by the same transport means;
the target access sequence scheduling step allocates an access sequence for the target points in each cluster set, and the transport means where the cluster set is located accesses according to the allocation sequence to complete the baggage delivering task.
Further, the destination allocation scheduling step includes the steps of:
1.1 taking initial positions of m transport means as cluster heads, and carrying out k-means clustering to obtain m clustering sets, wherein the k-means clustering use distance is space cost, and the space cost is running time between destinations. The destination includes baggage and travel Li Dedian, i.e., the location where each vehicle needs to pass; the driving time is estimated by the distance and road condition, and is directly read by an interface provided by navigation software at present, such as hundred degrees and high germany.
1.2, counting the repetition times of the baggage delivering places in each clustering set obtained in the step 1.1, and taking the place with the largest repetition times as a main destination of the clustering set;
when m is greater than or equal to n: if all n destinations become the main destination of at least one transport, destination allocation scheduling is completed, i.e. the order to which the destination belongs is allocated; if at least one destination does not become the main destination of one or more transportation means, counting the occurrence times of the destination in all cluster sets, and modifying the main destination of the cluster set with the largest occurrence times of the destination into the destination until all n destinations become the main destination of at least one transportation means;
when m < n: setting a destination k with the highest occurrence number in each cluster set as a main destination, wherein k is increased from 1 until all n destinations become the main destination of at least one transport means;
1.3, setting a non-primary destination in each cluster set as n_d, setting a cluster set with a primary destination as n_d as m_d, comparing the shortest distance between the non-primary destination in each cluster set and a cluster set with the primary destination as n_d, wherein the place comprises a baggage taking place and a baggage delivering place, and if the shortest distance is smaller than the average distance between the place and other places in the current cluster set, moving the place n_d from the current cluster set to the cluster set m_d; thus, the clustering is completed.
Further, the destination access sequence scheduling step includes the steps of:
2.1, p destinations are arranged in each cluster set, the destinations comprise baggage taking places and delivery lines Li Dedian, travel time between the current place of the transport means and all the destinations without assigned access sequences is compared one by one, the destination with the shortest travel time is taken as the next station access place and assigned access sequence, and the place is taken as the current place of the transport means, and the steps are repeated until all the p destinations are assigned corresponding access sequences;
2.2 calculating the time tp of arrival of the transport at each destination according to the destination access sequence allocated in step 2.1, and calculating the difference td between tp and the time tr required by the order, the required time for the order being the required arrival time provided when the customer submitted the baggage retrieval information, i.e. generated the baggage retrieval order, and the total completion time Ta:the total completion time refers to the total time for the transport to sequentially access all destinations according to the assigned access order; the travel time is directly read by an interface provided by the navigation software as described above, such as hundred degrees, germany.
2.3 define the exclusion set Q and initialize to the null set:
for all destinations excluding the set Q, when td is less than or equal to 0, keeping the current access order unchanged; when td > 0: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, the advance is not effective, i.e. no advance is performed;
if td is not reduced, the forward shift is not effective, i.e. the forward shift is not performed, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
2.4, comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order requirement time tr, if yes, finishing the steps, and finishing the distribution and scheduling of the destination access sequence; if not, the destination with the largest tr-tp value is rejected, and the step is carried out again until the estimated access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
Example 2
In the destination allocation and dispatch step, step 1.1 takes m destinations (including baggage and line Li Dedian) as cluster heads, and performs k-means clustering to obtain m cluster sets, where the distance used for k-means clustering is a time cost, and the time cost is a time difference between required delivery times for each baggage delivery order.
The time differences are compared in step 1.3: comparing the time difference of the places between the non-primary destination n_d and the cluster set m_d with the primary destination n_d in each cluster set, specifically:
comparing the time difference of the places between the non-primary destination n_d and the cluster set m_d with the primary destination n_d in each cluster set, specifically: setting the main destination of the clustering set J as d, for a place e (setting the destination corresponding to the place as q) with the destination not being d in the clustering set J, calculating the shortest distance from e to the place in the clustering set L with the main destination of q, and if the shortest distance is smaller than the average distance from e to the place in the clustering set J, moving e from the J set to the L; and repeating the step until the set of all orders is no longer changed and clustering is completed.
Example 3
The difference from example 1 is that: in this embodiment, the k-means clustering in step 1.1 uses the distance from the space cost to the destination; the destination includes baggage and travel Li Dedian, i.e., the location where each vehicle needs to pass.
In step 1.3: either the shortest distance of places between the non-primary destination n_d in each cluster set and the cluster set m_d with primary destination n_d can be compared in step 1.3 as described in example 1 or the time difference of places between the non-primary destination n_d in each cluster set and the cluster set m_d with primary destination n_d can be compared in step 1.3 as described in example 2.
Example 4
The difference from example 1 is that: in this embodiment, the step 2.3 is:
setting the baggage arrival time threshold to Td:
define the exclusion set Q and initialize to the null set: for all destinations excluding the set Q, when Td is less than or equal to Td, keeping the current access order unchanged; when Td > Td: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, the advance is not effective, i.e., no advance is performed;
if td is not reduced, the forward shift is not effective, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
2.4, comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order request time tr-Td, if yes, finishing the steps; if not, the destination with the largest tr-tp value is rejected and then is compared again until the expected access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
In this embodiment, by setting the threshold Td, a certain time is set for baggage handover between transportation means, and other situations that need to be considered in practical applications, so that the baggage picking and delivering scheduling method has more practicability and convenience in practical applications.
Example 5
The difference from example 1 is that: in the present embodiment, the order combining step is performed before the destination allocation scheduling step and the destination access scheduling step are performed: and when orders with the same places and different required delivery times are subjected to, if the time difference is not greater than T, combining the two orders, and taking the earlier time requirement as the time requirement of the combined order, wherein the time requirement is the time requirement submitted when a customer submits the baggage to take the order. The places are the same, namely a baggage taking place and a delivery Li Dedian, and any place of one order is the same as any place of other orders: t is an artificial set value, and is determined according to conditions such as a specific order busy condition and road conditions on the same day, and is determined to be half an hour in the embodiment.
Claims (8)
1. A baggage picking and delivering scheduling method of a plurality of transportation means with multiple destinations, wherein the baggage picking and delivering order submitted by a customer comprises n baggage delivering destinations, and the baggage picking and delivering task is completed by m transportation means, which is characterized in that: the method comprises a destination allocation scheduling step and a destination access sequence scheduling step:
the destination allocation and scheduling step divides n destinations into m cluster sets through clusters, allocates the m cluster sets to m transport means, and each transport means corresponds to one cluster set, wherein the clusters enable the baggage taking place and the baggage delivering line Li Dedian to be the same in the baggage taking order received by the same transport means;
the destination access sequence scheduling step allocates an access sequence for the destination points in each cluster set, and the transport means with the cluster set accesses according to the access sequence to complete the baggage delivering task;
the destination allocation scheduling step comprises the following steps:
1.1, taking any m destinations, wherein the destinations comprise taking initial positions of baggage and baggage places or m transport means as cluster heads, and carrying out k-means clustering to obtain m clustering sets, wherein the using distance of the k-means clustering is space cost or time cost;
1.2, counting the repetition times of the baggage delivering places in each clustering set obtained in the step 1.1, and taking the place with the largest repetition times as a main destination of the clustering set;
when m is greater than or equal to n: if all n destinations become the primary destination of at least one vehicle, destination allocation scheduling is complete; if at least one destination does not become the main destination of one or more transportation means, counting the occurrence times of the destination in all cluster sets, and modifying the main destination of the cluster set with the largest occurrence times of the destination into the destination until all n destinations become the main destination of at least one transportation means;
when m < n: setting a destination k with the highest occurrence number in each cluster set as a main destination, wherein k is increased from 1 until all n destinations become the main destination of at least one transport means;
1.3 comparing the shortest distance between the non-primary destination n_d in each cluster set and the cluster set m_d with primary destination n_d, if the shortest distance is smaller than the average distance from the place to other places in the current cluster set, moving the place n_d from the current cluster set to the cluster set m_d 。
2. A multi-destination, multi-conveyance baggage handling and dispatch method according to claim 1, wherein: the k-means clustering in the step 1.1 uses the space cost as the travel time between the destinations or the distance between the destinations.
3. A multi-destination, multi-conveyance baggage handling and dispatch method according to claim 1, wherein: the k-means cluster in step 1.1 uses the time cost from the time cost to the time difference between the arrival time required for each baggage retrieval order.
4. A multi-destination, multi-conveyance baggage handling and dispatch method according to claim 1, wherein: the step 1.3 is as follows: comparing the time difference of the places between the non-primary destination n_d and the cluster set m_d with the primary destination n_d in each cluster set, specifically: setting a main destination of a clustering set J as d, setting a destination corresponding to a place e in the J, which is not d, as q, calculating the shortest distance from e to a place in a clustering set L with the main destination q, and if the shortest distance is smaller than the average distance from e to the place in the J, moving e from the J set to the L; and repeating the step until the set of all orders is no longer changed and clustering is completed.
5. A multi-destination, multi-vehicle baggage handling and dispatch method according to any one of claims 1, 2, 3, or 4, wherein: the destination access sequence scheduling step comprises the following steps:
2.1, p destinations are arranged in each cluster set, the destinations comprise baggage taking places and delivery lines Li Dedian, travel time between the current place of the transport means and all the destinations without assigned access sequences is compared one by one, the destination with the shortest travel time is taken as the next station access place and assigned access sequence, and the place is taken as the current place of the transport means, and the steps are repeated until all the p destinations are assigned corresponding access sequences;
2.2 according to the destination access sequence assigned in step 2.1, calculating the time tp for the transport to reach each destination and the difference td between tp and the time tr required for the order, and the total completion time Ta:
2.3 define the exclusion set Q and initialize to the null set:
for all destinations excluding the set Q, when td is less than or equal to 0, keeping the current access order unchanged; when td > 0: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, then the advance is not effective;
if td is not reduced, the forward shift is not effective, i.e. the forward shift is not performed, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
2.4, comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order requirement time tr, if yes, finishing the steps, and finishing the distribution and scheduling of the destination access sequence; if not, the destination with the largest tr-tp value is rejected, and the step is carried out again until the estimated access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
6. The multi-destination, multi-conveyance baggage handling and dispatch method of claim 5, wherein: in the step 2.3, the following steps are:
setting the baggage arrival time threshold to Td:
define the exclusion set Q and initialize to the null set: for all destinations excluding the set Q, when Td is less than or equal to Td, keeping the current access order unchanged; when Td > Td: the access order of the destinations is advanced by 1 bit, and then td and the total completion time Ta of all the destinations are recalculated:
if td decreases and Ta does not increase, the next advance is effected and step 2.2 is returned;
if td decreases but Ta increases, then the advance is not effective;
if td is not reduced, the forward shift is not effective, the destination is added into the exclusion set Q, and the step returns to the step 2.2;
the step 2.4 is as follows: comparing whether the expected arrival time tp of all the destinations in each cluster set is within the order request time tr-Td, if yes, finishing the steps; if not, the destination with the largest tr-tp value is rejected and then is compared again until the expected access time tp of the destination in all the cluster sets is within the required time tr, and the order corresponding to the rejected destination is refused.
7. A method of baggage claim 1-4,6 for a multi-destination, multi-vehicle baggage claim, wherein: an order merging step is performed before the destination allocation scheduling step and the destination access scheduling step are performed: when orders with the same place and different time are required to be delivered, if the time difference is not greater than T, the two orders are combined, and the earlier time requirement is taken as the time requirement of the combined order.
8. A multi-destination, multi-vehicle baggage handling and dispatch method according to claim 5, wherein: an order merging step is performed before the destination allocation scheduling step and the destination access scheduling step are performed: when orders with the same place and different time are required to be delivered, if the time difference is not greater than T, the two orders are combined, and the earlier time requirement is taken as the time requirement of the combined order.
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