CN105260796A - Large scale industrial meta-heuristic multi-addressing system - Google Patents
Large scale industrial meta-heuristic multi-addressing system Download PDFInfo
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- CN105260796A CN105260796A CN201510678802.2A CN201510678802A CN105260796A CN 105260796 A CN105260796 A CN 105260796A CN 201510678802 A CN201510678802 A CN 201510678802A CN 105260796 A CN105260796 A CN 105260796A
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Abstract
The invention relates to the electronic information technical field, especially to a large scale industrial meta-heuristic multi-addressing system which comprises a system foreground information obtaining module, a noise interference point rejecting module, an addressing boundary searching module, an alternative area addressing sub-boundary generating module, an addressing representative point generating module, a non-addressing area logic determining and calculating module, an object function module, an alternative area module for storing optimal and secondary sub- boundaries, and an iteration circulating calculating module. The system employs a meta-heuristic algorithm in a large scale industrial addressing filed, thoroughly solves the problem that a present system can not perform real-time interactive calculation with navigation, or perform limitless large scale multi-addressing at once, or avoid a non-addressing area, and substantially improves calculating precision, problem calculability and solubility, and system recommended result maneuverability.
Description
Technical field
The present invention relates to electronic information technical field, particularly relate to a kind of many site selection systems of meta-heuristic of large-scale industry.
Background technology
Meta-heuristic algorithms, refers to by handling or manage one group of low layer heuritic approach, to obtain new heuritic approach and to utilize computer science and technology, thus solves New Algorithm and the technology that large-scale industry calculates a difficult problem.
Multiselect location is solution that is disposable, that simultaneously calculate multiple optimal location.Traditional addressing only exports an optimal location at every turn, and can there is interference between multiposition.Multiselect location can solve simultaneously, and " where best position is " with " how many positions are best " this two problems.
Addressing is very classical industry and mathematical problem.Such as, the transit depot addressing etc. of the shop addressing of supermarket or convenience store, the Mesh Point Selected Location of bank, manufacturing plant siting, logistics express company.At present, the addressing algorithm on market is mainly Location Selection by Gravity Method (Bao Chuan, 2012), namely carries out finding geometric center of gravity thus reaching the shortest object of total air line distance according to the geographic distribution of the object of client or location-based service to be selected.The advantage of this site selecting method is directly simple, drawback be calculate accuracy low (cannot and navigation type system carry out interactive computing etc.), cannot be used for industry extensive class calculates (variable is between 200 to 10000), cannot consider can not addressing region.
Summary of the invention
According to Problems existing in prior art and algorithm, now provide a kind of meta-heuristic of large-scale industry many site selection systems, thus improve the precision that calculates and provide the intelligent system that really can solve actual many location problems for industry.
Technique scheme specifically comprises:
System foreground obtaining information: because this is an intelligent system, therefore, first page system will be clear that user wants to solve what problem, has what requirement.Therefore, the first step is the foundation class information being obtained some necessity by system foreground, such as: treat all object's positions that addressing point serves, can not addressing region, computational accuracy and target component (minimizing cost or minimizing service duration) etc.
Reject noise jamming point: the noise jamming point finding out impact definition border according to the characteristic distributions of point and the discrete analysis theory of mathematics, thus improve the precision and computing velocity that calculate.
Find addressing border: define addressing border according to the covering point after optimizing, thus improve addressing efficiency.
Produce the sub-border of alternative area addressing: according to the addressing position number exporting optimum solution, calculate the cutting mode of subregion, and a large regions is divided into some zonules, this is the classical BreakandConquer mode of thinking, a large problem is disassembled as after some minor issues, then solves.
Generate addressing representative point: find out in the zone can represent region characteristic point to represent this region.This is a thought of fanning out from point to area, and simplifies problem by finding the individuality that can represent colony.
Can not addressing region Logic judgment and calculating: come judging area whether can not addressing region according to representative point, although representative point contains the important attribute in region, but representative point can not embody all character in region completely, such as, even if judge that representative point is can not addressing region, whole region can not be affirmed all can not addressing region, therefore, we can carry out secondary judgement, to improve the accuracy of judgement, the probability missing optimum solution are reduced 30%-50%.
Optimum and the sub-border of suboptimum being saved to alternative area: so-called optimum or suboptimal solution, is relative target function, and in all solutions, which more meets the target of objective function.Why to retain suboptimal solution, or because the reason of Points replacing surfaces.Although representative point contains the important attribute in region, but representative point can not embody all character in region completely, even if certain representative point is optimum relative to other representative points, this do not represent a little all than this point poor, therefore, we can retain suboptimal solution, to improve the accuracy of judgement, the probability missing optimum solution are reduced 30%-50% again.
Step 3 is repeated to alternative area, until meet computational accuracy: this is a continuous test, the process of constantly search downwards.Once, granularity is a little order of magnitude just, and test number of times is more, and precision is less in every test, calculates duration longer.
Useful effect of the present invention is: native system adopts the algorithm of meta-heuristic in large-scale industry addressing field, thoroughly solve existing system cannot calculate with navigation real-time, interactive, cannot disposable unconfined extensive multiselect location and cannot avoid can not the problem in addressing region, result substantially increases the operability of the precision of calculating, the calculability of problem and solubility, system recommendation result.
Accompanying drawing explanation
Fig. 1 is case study on implementation and the flow process of the many site selection systems of meta-heuristic of a kind of large-scale industry of the present invention.
Fig. 2 is the system foreground obtaining information of the meta-heuristic multiselect location System Implementation case of a kind of large-scale industry of the present invention.
Fig. 3 is the rejecting noise jamming point of the meta-heuristic multiselect location System Implementation case of a kind of large-scale industry of the present invention.
Fig. 4 is the searching addressing border of the meta-heuristic multiselect location System Implementation case of a kind of large-scale industry of the present invention.
Fig. 5 is the sub-border of generation alternative area addressing of the meta-heuristic multiselect location System Implementation case of a kind of large-scale industry of the present invention.
Fig. 6 is the generation addressing representative point of the meta-heuristic multiselect location System Implementation case of a kind of large-scale industry of the present invention.
Wherein,
represent the point that addressing place is served;
representative can not addressing region;
represent the representative point that addressing Area generation goes out;
representative edge boundary line or line of cut.
concrete embodiment
Below in conjunction with the accompanying drawing in the invention process, carry out clear, complete description to the technical scheme in the invention process case, obviously, described case study on implementation is only the present invention's part case study on implementation, instead of whole case study on implementation.Based on the case study on implementation in the present invention, the every other case study on implementation that those of ordinary skill in the art obtain under the prerequisite not making creative work, all belongs to protection scope of the present invention.
It should be noted that, when not conflicting, the case study on implementation in the present invention and the feature in case study on implementation can combine mutually.
Below in conjunction with accompanying drawing and concrete case study on implementation, the present invention will be further described, but not as limiting to the invention.
In existing technology, site selecting method based on gravity model appoach calculates accuracy low (cannot and navigation type system carry out interactive computing etc.), cannot be used for that the extensive class of industry calculates (variable is between 200 to 10000), cannot consider can not addressing region, therefore, solution Siting of Industry problem that cannot be real.
Implementing procedure as shown in Figure 1,
In better case study on implementation of the present invention, as Fig. 2, system foreground obtaining information: by dock with other system or user uploads all object longitudes and latitudes treating that addressing point is served on foreground, utilizing polygon to draw several at the interface, foreground of system can not addressing region, on system foreground by drop-down seletion calculation precision and target component (minimizing cost or minimizing service duration)
In better case study on implementation of the present invention, as Fig. 3, reject noise jamming point: calculate mean longitude, mean latitude, longitude standard deviation and the latitude standard deviation for the treatment of all objects that addressing point is served.To the mean longitude ± 2 times standard deviation of longitude a little and colony compare, if between [mean longitude-2 times of standard deviations, mean longitude+2 times of standard deviations], so this point is deposited the set of efficient frontier point, otherwise defining this point is noise point, do not add the set of efficient frontier point.
In better case study on implementation of the present invention, as Fig. 4, find addressing border: first find out the point containing maximum longitude, maximum latitude, minimum longitude, minimum latitude in the efficient frontier point set treating that addressing point is served.Then, draw longitude and latitude parallel lines with these frontier points, thus construct addressing border and scope.
In better case study on implementation of the present invention, as Fig. 5, produce the sub-border of alternative area addressing: first, determine the number of subregion according to the number of optimum point.Subregion number=N^2, N^2 is a value just greater than 2 times of optimum point numbers.N is the quantity of original region transverse and longitudinal being cut.Such as, when optimum point number is 7, so, the square value just greater than 2*7 (=14) is 16(4^2), therefore, in this case, subregion number is 16, and transverse and longitudinal is each on average cuts into 4 parts.These lines of cut are the border of subregion.
In better case study on implementation of the present invention, as Fig. 6, generate addressing representative point: the representative point of geometric center of gravity as this region choosing subregion.The mean value of representative point longitude=subzone boundaries longitude; The mean value of representative point latitude=subzone boundaries latitude.
Can not addressing region Logic judgment and calculating: first, judge addressing representative point whether can not addressing region, as no, then calculating target function result is sorted; In this way, then whether judge this representative point further " occurred can not addressing region ", then this region is eliminated in this way, as no, then preserve this region to alternative area and is labeled as " occurred can not addressing region ".
Calculate the objective function of each representative point:
Objective function=minimize (total cost) or minimize (always transporting duration);
The finishing facility input cost in total cost=total transport cost+total year rent cost+total personnel cost+always addressing place;
Total transport cost=summation (single kilometer of transportation cost of the corresponding vehicle of navigation distance * of each bar transportation route);
Within total year, change the WACC that rent cost data derives from house property investigational data storehouse, each location, each city and enterprise;
Personnel cost (the personnel depaly information database data from each addressing place)+total driver's cost (data from different industries personnel wage investigational data storehouse, each department) in total personnel cost=total addressing field;
The average salary of the corresponding regional corresponding human person of personnel depaly * in personnel cost in total addressing field=each addressing place;
Driver's average salary (driver's average salary investigational data storehouse of different regions different automobile types) of rostered staff factor (the staffing data storehouse data from different automobile types) the * corresponding vehicle vehicle number * different automobile types of total driver's cost=different automobile types.
The objective function result of each representative point of difference is sorted.
Optimum and the sub-border of suboptimum are saved to alternative area database.
Step 3 is repeated, until meet computational accuracy to alternative area.
Claims (8)
1. the many site selection systems of the meta-heuristic of large-scale industry, is characterized in that, comprising:
System foreground obtaining information module, for obtaining some elemental user demand informations of calculating;
Reject noise jamming point module, for finding out the point of interfering well cluster and calculating and being rejected;
Finding addressing boundary module, for defining addressing border, thus improving addressing efficiency;
Produce the sub-boundary module of alternative area addressing, for resolution problem, to reduce the solution difficulty of system problem;
Generate addressing representative point module, for continuity problem is converted into dispersed problem, thus reduce the difficulty of system problem further;
Can not addressing region Logic judgment and computing module, judge potential optimum point whether can not addressing region for computational analysis;
Objective function module, for seeking minimizing or the maximization of service quality of cost;
Optimum and the sub-border of suboptimum are saved to alternative area module, for the manufacture of an alternative area thesaurus;
Iterative loop computing module, for going deep into iterative computation to improve the precision of result of calculation.
2. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, described system foreground obtaining information module comprises:
Treat all object location information that addressing point is served, for obtaining service object's latitude and longitude information;
Can not addressing area information, for calling in later stage of addressing region Logic judgment and computing module;
Computational accuracy and target component information, use for controlling calculation duration and Choice.
3. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, described rejecting noise jamming point module comprises:
The characteristic distributions of point and the discrete analysis theory of mathematics, for finding out the noise jamming point on impact definition border.
4. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, described searching addressing boundary module comprises:
Find out the point containing maximum longitude, maximum latitude, minimum longitude, minimum latitude in the efficient frontier point set treating that addressing point is served, to find out frontier point;
Draw longitude and latitude parallel lines with frontier point, thus construct addressing border and scope.
5. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, the sub-boundary module of described generation alternative area addressing comprises:
The number algorithm of subregion is determined, to determine the most effective region cutting mode according to the number of optimum point.
6. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, described generation addressing representative point module comprises: the Algorithms of Selecting of representative point, the mean value of representative point longitude=subzone boundaries longitude; The mean value of representative point latitude=subzone boundaries latitude, better to extract provincial characteristics.
7. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, is characterized in that, describedly can not comprise with calculating by addressing region Logic judgment: once judge and secondary mark memory function.
8. the many site selection systems of meta-heuristic of large-scale industry as claimed in claim 1, it is characterized in that, the objective function module of each representative point of described calculating comprises:
Total transport cost structure, for calculating transportation cost;
The WACC of house property investigational data storehouse, each location, each city and enterprise, for calculating rent cost;
The personnel depaly information database in each addressing place and different industries personnel wage investigational data storehouse, each department, for computing staff's cost;
Driver's average salary investigational data storehouse of different regions different automobile types, for calculating driver's cost;
Place decorating apparatus drops into configuration database, for calculating total addressing place finishing and equipment investment cost.
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| CN112669340A (en) * | 2020-12-23 | 2021-04-16 | 佛山市城市规划设计研究院 | GIS big data analysis-based public facility site selection method and system |
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| CN103984997A (en) * | 2014-05-29 | 2014-08-13 | 国家电网公司 | Transmission project site and line selecting method based on GIS space information |
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| CN103984997A (en) * | 2014-05-29 | 2014-08-13 | 国家电网公司 | Transmission project site and line selecting method based on GIS space information |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110245818A (en) * | 2019-01-21 | 2019-09-17 | 北京航空航天大学 | Hub location method and apparatus |
| CN112669340A (en) * | 2020-12-23 | 2021-04-16 | 佛山市城市规划设计研究院 | GIS big data analysis-based public facility site selection method and system |
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Application publication date: 20160120 |