CN108846513A - A kind of delivery job order head and the tail optimization method and system based on GIS - Google Patents

A kind of delivery job order head and the tail optimization method and system based on GIS Download PDF

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CN108846513A
CN108846513A CN201810579675.4A CN201810579675A CN108846513A CN 108846513 A CN108846513 A CN 108846513A CN 201810579675 A CN201810579675 A CN 201810579675A CN 108846513 A CN108846513 A CN 108846513A
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葛春霖
宗学宝
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Inspur Software Co Ltd
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Abstract

The invention discloses a kind of delivery job order head and the tail optimization method and system based on GIS, for logistics distribution process, prepare basic data first, acquire all Customer Location data to be dispensed, then pass through GIS technology, Customer Location is identified in a manner of coordinate system in map, all Customer Locations are target point;Obtain the dispatching head and the tail family of several delivery car groups, i.e., the target point reached at first and the target point finally reached;All paths for obtaining head and the tail family target point are calculated by deployment services device, and it is more reasonable which delivery car group is belonged to according to the adjacent family Distance Judgment head and the tail family of route result.A kind of delivery job order head and the tail optimization method and system based on GIS of the invention is compared with prior art, solves the adjacent delivery car group track cross bring dispatching inefficiency of former logistics distribution, the problem of wasting of resources, improve the delivery efficiency of deliveryman, customer satisfaction is improved, time cost and logistics cost are saved.

Description

A kind of delivery job order head and the tail optimization method and system based on GIS
Technical field
The present invention relates to logistics distribution technical field, specifically a kind of practical delivery job order based on GIS Head and the tail optimization method and system.
Background technique
In logistics distribution process, how to realize accurate dispatching, how to save logistics cost to greatest extent, match to improve Efficiency and customer satisfaction are sent, is a great problem that the field needs to solve.
And in logistics distribution process, it is divided into different delivery tasks by useful load for a series of orderly target points When, target point similar in adjacent delivery car group delivery position, it is possible that delivery track cross, can not accomplish that nearest delivery is former Then, result in waste of resources, logistics cost improve the case where.
Based on the above reasons, this method calculates road service by calling and calculates essence according to a series of longitude and latitude of distribution points Quasi- dispatching route and mileage, to judge more excellent delivery scheme.To improve the satisfaction of dispatching efficiency and client, reach section Save the purpose of logistics cost.
Summary of the invention
Technical assignment of the invention is place against the above deficiency, provides a kind of practical delivery based on GIS and appoints The single head and the tail optimization method of business and system.
A kind of delivery job order head and the tail optimization method based on GIS is used for logistics distribution process, and realization process is,
One, prepare basic data first, that is, acquire all Customer Location data to be dispensed, it, will then by GIS technology Customer Location is identified that all Customer Locations are target point in map in a manner of coordinate system;
Two, the dispatching head and the tail family of several delivery car groups, i.e., the target point reached at first and the target point finally reached are obtained;
Three, all paths for obtaining head and the tail family target point are calculated by deployment services device, according to the adjacent family distance of route result It is more reasonable to judge which delivery car group head and the tail family belongs to, i.e., by reselecting first family, tail family, adjusts corresponding delivery task, Complete the selection of delivery car group.
Target point in the step 1 is to be stored in server database after being collected in advance, and put down by arcgis Platform completes map and path computing shows process.
First family adjustment in the step 3 carries out in the following manner:Selected first family is apart from a upper delivery car Closer and upper vehicle group non-overloading is organized, and is more than M kilometers apart from next family more than first family, M here is settable parameter.
Tail family adjustment in the step 3 carries out in the following manner:Selected tail family is apart from next delivery car Closer and next vehicle group non-overloading is organized, and is more than M kilometers apart from a upper family more than tail family, M here is settable parameter.
In the step 3, when head and the tail family adjusts delivery car group, specifically adjusted by following formula:
Rear car is adjusted toward front truck:(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car:((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
A kind of delivery job order head and the tail optimization system based on GIS, including,
Recording module, for basic data to be entered into server, which refers to all clients to be dispensed Position data;
Map display module Customer Location is identified in a manner of coordinate system in map, Suo Youke by GIS technology Family position is target point, and identifies the dispatching head and the tail family of all delivery car groups, i.e., the target point reached at first and finally arrives The target point reached;
Computing module, the cartographic information that display module is shown according to the map calculate all paths for obtaining head and the tail family target point, root It is more reasonable to belong to which delivery car group according to the adjacent family Distance Judgment head and the tail family of route result;
Distribution module reselects first family, the tail family of delivery car group according to the calculated result of computing module, and adjustment is sent accordingly Goods task.
The map display module, computing module completes map using arcgis platform and path computing shows process.
In the computing module, first family reselects to carry out in the following manner:Selected first family is apart from upper one Delivery car group is closer and upper vehicle group non-overloading, and be more than first family apart from next family is more than M kilometers, and M here is settable Parameter.
In the computing module, tail family reselects to carry out in the following manner:Selected tail family is apart from next Delivery car group is closer and next vehicle group non-overloading, and be more than tail family apart from a upper family is more than M kilometers, and M here is can set Set parameter.
The computing module selects specific delivery car group by following formula, is then selected again according to the delivery car group of selection Select first family, tail family:
Rear car is adjusted toward front truck, i.e., when the delivery car group that current target point is distributed being adjusted to upper delivery car group:
(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car, i.e., when the delivery car group that current target point is distributed being adjusted to next delivery car group:
((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
Compared to the prior art a kind of delivery job order head and the tail optimization method and system based on GIS of the invention, has Following beneficial effect:
A kind of delivery job order head and the tail optimization method and system based on GIS of the invention, the present invention combine practical logistics delivery Business is solved in logistics distribution process using based on the technology for calculating road service, adjacent delivery car group track cross bring dispatching Low efficiency, the problem of causing logistic resources to waste, reach accurate delivery, improve the delivery efficiency of deliveryman, improve client Satisfaction saves time cost and logistics cost, has practical, applied widely, easy to spread feature.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis The attached drawing of offer obtains other attached drawings.
Attached drawing 1 is the implementation example figure of present system.
Specific embodiment
Scheme in order to enable those skilled in the art to better understand the present invention, With reference to embodiment to this Invention is described in further detail.Obviously, described embodiments are only a part of the embodiments of the present invention, rather than all Embodiment.Based on the embodiments of the present invention, those of ordinary skill in the art institute without making creative work The every other embodiment obtained, shall fall within the protection scope of the present invention.
The present invention provides a kind of, and the delivery job order head and the tail optimization method based on GIS is realized for logistics distribution process Process is as follows:
Basic data:
Position data prepares:By Customer Location data(Hereinafter referred to as target point)It is collected in advance.
Position processing:The coordinate combination current map coordinate system of target point is deviated, respective coordinates system is converted into Coordinate points.
Business model:
The constraint condition of most critical in delivery process:The position data of target point.The position data of target point refers to the ground of client Position is managed, industry relatively fixed for customer group, client's coordinate position is also that can acquire in advance and be saved in lane database 's.
Head and the tail optimize:By the head and the tail family of adjacent delivery car group(It can be the family N)The high performance server portion of call by location The arcgis of administration calculates road service or other calculate road service and perfect map datum carries out calculation road, according to the phase for calculating road result The Distance Judgment head and the tail family at adjacent family(It can be the family N)It is more reasonable to belong to which delivery car group, then adjusts corresponding delivery task.
Further, the specific implementation step of the above process is,
One, prepare basic data first, that is, acquire all Customer Location data to be dispensed, it, will then by GIS technology Customer Location is identified that all Customer Locations are target point in map in a manner of coordinate system;
Two, the dispatching head and the tail family of several delivery car groups, i.e., the target point reached at first and the target point finally reached are obtained;
Three, all paths for obtaining head and the tail family target point are calculated by deployment services device, according to the adjacent family distance of route result It is more reasonable to judge which delivery car group head and the tail family belongs to, i.e., by reselecting first family, tail family, adjusts corresponding delivery task, Complete the selection of delivery car group.
Target point in the step 1 is to be stored in server database after being collected in advance, and put down by arcgis Platform completes map and path computing shows process.
First family adjustment in the step 3 carries out in the following manner:Selected first family is apart from a upper delivery car Closer and upper vehicle group non-overloading is organized, and is more than M kilometers apart from next family more than first family, M here is settable parameter.
Tail family adjustment in the step 3 carries out in the following manner:Selected tail family is apart from next delivery car Closer and next vehicle group non-overloading is organized, and is more than M kilometers apart from a upper family more than tail family, M here is settable parameter.
In the step 3, when head and the tail family adjusts delivery car group, specifically adjusted by following formula:
Rear car is adjusted toward front truck:(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car:((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
As shown in Fig. 1, a kind of delivery job order head and the tail optimization system based on GIS, including,
Recording module, for basic data to be entered into server, which refers to all clients to be dispensed Position data;
Map display module Customer Location is identified in a manner of coordinate system in map, Suo Youke by GIS technology Family position is target point, and identifies the dispatching head and the tail family of all delivery car groups, i.e., the target point reached at first and finally arrives The target point reached;
Computing module, the cartographic information that display module is shown according to the map calculate all paths for obtaining head and the tail family target point, root It is more reasonable to belong to which delivery car group according to the adjacent family Distance Judgment head and the tail family of route result;
Distribution module reselects first family, the tail family of delivery car group according to the calculated result of computing module, and adjustment is sent accordingly Goods task.
The map display module, computing module completes map using arcgis platform and path computing shows process.
In the computing module, first family reselects to carry out in the following manner:Selected first family is apart from upper one Delivery car group is closer and upper vehicle group non-overloading, and be more than first family apart from next family is more than M kilometers, and M here is settable Parameter.
In the computing module, tail family reselects to carry out in the following manner:Selected tail family is apart from next Delivery car group is closer and next vehicle group non-overloading, and be more than tail family apart from a upper family is more than M kilometers, and M here is can set Set parameter.
The computing module selects specific delivery car group by following formula, is then selected again according to the delivery car group of selection Select first family, tail family:
Rear car is adjusted toward front truck, i.e., when the delivery car group that current target point is distributed being adjusted to upper delivery car group:
(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car, i.e., when the delivery car group that current target point is distributed being adjusted to next delivery car group:
((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
System provided by the invention combines practical logistics delivery business, solves the adjacent delivery car group rail of former logistics distribution The problem of mark intersection bring dispatching inefficiency, the wasting of resources, the delivery efficiency of deliveryman is improved, customer satisfaction is improved Degree, saves time cost and logistics cost.
The foregoing is merely presently preferred embodiments of the present invention, and scope of patent protection of the invention includes but is not limited to above-mentioned tool Body embodiment, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all include Within scope of patent protection of the invention.
The technical personnel in the technical field can readily realize the present invention with the above specific embodiments,.Herein Apply that a specific example illustrates the principle and implementation of the invention, the explanation of above example is only intended to help Understand method and its core concept of the invention.It should be pointed out that for those skilled in the art, not taking off , can be with several improvements and modifications are made to the present invention under the premise of from the principle of the invention, these improvement and modification also fall into this In invention scope of protection of the claims.

Claims (10)

1. a kind of delivery job order head and the tail optimization method based on GIS is used for logistics distribution process, which is characterized in that it is realized Process is,
Prepare basic data first, that is, acquires all Customer Location data to be dispensed, it, will be objective then by GIS technology Family position is identified that all Customer Locations are target point in map in a manner of coordinate system;
Obtain the dispatching head and the tail family of several delivery car groups, i.e., the target point reached at first and the target point finally reached;
All paths for obtaining head and the tail family target point are calculated by deployment services device, according to the adjacent family Distance Judgment of route result It is more reasonable which delivery car group head and the tail family belongs to, i.e., by reselecting first family, tail family, adjusts corresponding delivery task, complete The selection of delivery car group.
2. a kind of delivery job order head and the tail optimization method based on GIS according to claim 1, which is characterized in that described Target point in step 1 be stored in server database after being collected in advance, and by arcgis platform complete map and Path computing shows process.
3. a kind of delivery job order head and the tail optimization method based on GIS according to claim 1, which is characterized in that described First family adjustment in step 3 carries out in the following manner:Selected first family it is closer apart from a upper delivery car group and on One vehicle group non-overloading, and be more than M kilometers apart from next family more than first family, M here is settable parameter.
4. a kind of delivery job order head and the tail optimization method based on GIS according to claim 1, which is characterized in that described Tail family adjustment in step 3 carries out in the following manner:Selected tail family it is closer apart from next delivery car group and under One vehicle group non-overloading, and be more than M kilometers apart from a upper family more than tail family, M here is settable parameter.
5. a kind of delivery job order head and the tail optimization method based on GIS according to claim 1, which is characterized in that described In step 3, when head and the tail family adjusts delivery car group, specifically adjusted by following formula:
Rear car is adjusted toward front truck:(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car:((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
6. a kind of delivery job order head and the tail optimization system based on GIS, which is characterized in that including,
Recording module, for basic data to be entered into server, which refers to all clients to be dispensed Position data;
Map display module Customer Location is identified in a manner of coordinate system in map, Suo Youke by GIS technology Family position is target point, and identifies the dispatching head and the tail family of all delivery car groups, i.e., the target point reached at first and finally arrives The target point reached;
Computing module, the cartographic information that display module is shown according to the map calculate all paths for obtaining head and the tail family target point, root It is more reasonable to belong to which delivery car group according to the adjacent family Distance Judgment head and the tail family of route result;
Distribution module reselects first family, the tail family of delivery car group according to the calculated result of computing module, and adjustment is sent accordingly Goods task.
7. a kind of delivery job order head and the tail optimization system based on GIS according to claim 6, which is characterized in that described Map display module, computing module completes map using arcgis platform and path computing shows process.
8. a kind of delivery job order head and the tail optimization system based on GIS according to claim 6, which is characterized in that described In computing module, first family reselects to carry out in the following manner:Selected first family is closer apart from a upper delivery car group And upper vehicle group non-overloading, and be more than M kilometers apart from next family more than first family, M here is settable parameter.
9. a kind of delivery job order head and the tail optimization system based on GIS according to claim 6, which is characterized in that described In computing module, tail family reselects to carry out in the following manner:Selected tail family is closer apart from next delivery car group And next vehicle group non-overloading, and be more than M kilometers apart from a upper family more than tail family, M here is settable parameter.
10. a kind of delivery job order head and the tail optimization system based on GIS according to claim 6, which is characterized in that described Computing module selects specific delivery car group by following formula, then reselects first family, tail family according to the delivery car group of selection:
Rear car is adjusted toward front truck, i.e., when the delivery car group that current target point is distributed being adjusted to upper delivery car group:
(Sn<N) && (Mn>M) && (Mn<M(n+1)) && ((Qpre+Qn)<=Q) == true;
Front truck is adjusted toward rear car, i.e., when the delivery car group that current target point is distributed being adjusted to next delivery car group:
((|Smax-Sn|)<N) && (M(n-1)>M) && (Mn>Mn+1) && (Qpre+Qn<=Q) && (Qn<=Q)== true;
In above-mentioned two formula, N, M are settable parameter, and N representative can correct amount, and M represents amendable spherical distance;Sn Represent existing customer serial number, Smax represents maximum serial number, i.e. tail family serial number, Mn represent current family and a upper family away from From, Qn represents the order volume of existing customer, and Qpre represents the useful load of a vehicle, and Qnext represents the useful load of next vehicle, Q represents standard amount;
In rear car into the formula that front truck adjusts, current sequence number is within the scope of the preceding family N, and current family is at a distance from next family More than M, and current family is closer from a upper family, and the order volume at current family moves on to front truck and do not overload, and all conditions must be same When meet;
In front truck into the formula that rear car adjusts, current sequence number is within the scope of the rear family N, and current family is at a distance from a upper family More than M, and current family is closer from next family, and the order volume at current family moves on to rear car and do not overload, and all conditions must be same When meet.
CN201810579675.4A 2018-06-07 2018-06-07 A kind of delivery job order head and the tail optimization method and system based on GIS Pending CN108846513A (en)

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CN105205556A (en) * 2015-09-18 2015-12-30 浪潮软件股份有限公司 Distribution optimization algorithm based on balanced task allocation
CN105184417A (en) * 2015-09-24 2015-12-23 国家电网公司 Distribution route optimization method and apparatus for metering devices
CN107437122A (en) * 2016-05-26 2017-12-05 北京三快在线科技有限公司 Determine that businessman dispenses the method and device of scope
CN107451702A (en) * 2017-08-15 2017-12-08 浪潮软件股份有限公司 A kind of method and device for the driving path for determining dispensing vehicle

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CN112978190A (en) * 2019-06-29 2021-06-18 深圳市海柔创新科技有限公司 Goods taking task allocation method and goods sorting system thereof
CN112907187A (en) * 2021-03-13 2021-06-04 深圳市土地公网络科技有限公司 Distribution route planning method and device, electronic equipment and storage medium

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