CN104573860B - A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method - Google Patents
A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method Download PDFInfo
- Publication number
- CN104573860B CN104573860B CN201410855815.8A CN201410855815A CN104573860B CN 104573860 B CN104573860 B CN 104573860B CN 201410855815 A CN201410855815 A CN 201410855815A CN 104573860 B CN104573860 B CN 104573860B
- Authority
- CN
- China
- Prior art keywords
- msub
- mrow
- order
- farm
- greenhouse
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 235000013311 vegetables Nutrition 0.000 title claims abstract description 123
- 238000000034 method Methods 0.000 title claims abstract description 28
- 239000000463 material Substances 0.000 claims abstract description 36
- 238000004519 manufacturing process Methods 0.000 claims abstract description 26
- 230000008901 benefit Effects 0.000 claims abstract description 9
- 238000010200 validation analysis Methods 0.000 claims abstract description 9
- 230000000007 visual effect Effects 0.000 claims abstract description 8
- 230000003466 anti-cipated effect Effects 0.000 claims abstract description 7
- 238000002513 implantation Methods 0.000 claims abstract description 7
- 238000012795 verification Methods 0.000 claims abstract description 6
- 230000002068 genetic effect Effects 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 5
- 230000036642 wellbeing Effects 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims 1
- 239000002689 soil Substances 0.000 abstract description 3
- 238000003967 crop rotation Methods 0.000 abstract description 2
- 210000004027 cell Anatomy 0.000 description 8
- 238000010586 diagram Methods 0.000 description 4
- 241000894007 species Species 0.000 description 3
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 1
- 241000607479 Yersinia pestis Species 0.000 description 1
- 229910002056 binary alloy Inorganic materials 0.000 description 1
- 210000000349 chromosome Anatomy 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000009335 monocropping Methods 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Animal Husbandry (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Development Economics (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method.Methods described includes：Input data, carries out data initialization；Input data is pre-processed and validation verification；Required according to customer order, be that place and implantation time, generation enterprise planting scheme scheduling result are planted in all order arrangements using intelligent heuristics algorithm；Visual presentation enterprise planting scheme scheduling result.The present invention is to meet the customer order demand of vegetable cultivation enterprise as target, while taking into full account the factors such as anticipated price, production cycle, labour and the goods and materials cost of each vegetable variety, soil crop rotation, transportation range, ensure while customer order demand is completed, to enable the planting scheme made to reach that Business Economic Benefit is maximized.The layout efficiency of large-scale vegetable cultivation enterprise vegetable cultivation plan can be effectively improved using the method for the invention, automation and the intelligent level of layout work is improved.
Description
Technical field
It is more particularly to a kind of to utilize Optimum Theory, decision support system the invention belongs to vegetable cultivation plan field
The theoretical method for realizing vegetable cultivation plan automatic editing with intelligent algorithm of system.
Background technology
In vegetable cultivation plan scheduling, it is necessary to consider the technical merit of practitioner, regional climate condition, soil
The influence factors such as condition, institution, preservation and freshness, the market demand, vegetable cultivation enterprise planting scheme scheduling problem is substantially
One nonlinear restriction optimization problem.Firstly, it is necessary to according to local working condition, vegetable species or kind labor cost
With goods and materials cost, technology complexity, the cultivated area of vegetables is determined；Secondly, it is necessary to consider that the market equilibrium supply of vegetables is asked
Topic, for example, noting stifled dull season, the busy season of hiding in season crops for rotation arrangement, extends time periods of supply, existing sharp market supply can more be carried
High economic benefit；Again, it is necessary to consider Seasonal, effective production season of this area should be made full use of, is noted with before
The convergence time of stubble, notes the rationally rotation of crops, it is to avoid similar vegetable continuous cropping, to mitigate the propagation of pest and disease damage and infect again afterwards；So
Afterwards, while appropriate vegetable species are arranged, the improved seeds of suitable local conditional plantation are selected as far as possible；Finally, use
New planting patterns or the new vegetable species of introduction or kind, notices that interlocal weather conditions difference and local consumption are practised
It is used, should small area plant experimentally it is successful on the basis of progressively develop again.Due to formulate the vegetables production schedule when, it is necessary to consider
Factor it is numerous, how to make the scientific and reasonable vegetables production schedule in resource constraint is one extremely complex and cumbersome
Work.
The conventional method that enterprise formulates the vegetables production schedule is, completely by manually carrying out layout according to personal experience, to meter
The requirement for drawing layout personnel is higher, and this method not only takes time and effort, and because the planting scheme of artificial layout often can not be same
When take into account the requirement of benefit, production capacity, cost savings, region, planting facility and the cropping pattern aspects such as rationally, cause to arrange
Planting scheme it is not scientific and reasonable enough.As current large-scale vegetables manufacturing enterprise is constantly to scale, specialization, intensive, mark
Standardization direction is developed, and traditional manual method of combination is difficult to the need for meeting enterprise scien` management.
The content of the invention
For above mentioned problem present in traditional vegetables production schedule formulating method, the invention provides a kind of large-scale vegetables
Enterprise's planting scheme automatic generation method is planted, this method can quickly generate scientific and rational kind according to relevant constraint
Plan scheduling scheme is planted, the operating efficiency of vegetable cultivation enterprise plan scheduling personnel is improved, realizes large-scale vegetable cultivation enterprise kind
Plant the automation and intellectuality of plan scheduling work.
In order to solve the above technical problems, the present invention uses following technical scheme.
A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method, comprises the following steps：
S1：Input data, carries out data initialization；
S2：To the input data in step S1, pre-processed and validation verification；
S3：Required according to customer order, using intelligent heuristics algorithm, during for all order arrangements plantation place and plantation
Between, generate enterprise's planting scheme scheduling result.
Further, described large-scale vegetable cultivation enterprise planting scheme automatic generation method, it is characterised in that described
The farm that large-scale vegetable cultivation enterprise is distributed in by several on diverse geographic location is constituted, and is designated as fm1,fm2,...,fmn；Its
In, each farm is divided into several sections, is designated as disth；Each section is made up of several greenhouses again, is designated as ghj, greatly
Canopy is the minimum plantation unit of enterprise；Each farm, section, greenhouse are owned by unique encodings in enterprise-wide, according to greenhouse
Coding can obtain belonging to section coding, according to section coding can obtain belonging to farm encode.
Further, the input data described in step S1 includes：Specify time interval Δ T, customer order list
OrderList, vegetable variety list VarietyList, kind production capacity list VarietyCapacityList, plantation code row
Table RuleList, the annual facility area list FacilityList in farm, labor cost information LaborCostList, goods and materials
Cost information InputsCostList, kind precedence information VarietyRankList etc..
Further, the time interval Δ T described in step S1 is using consecutive days as least unit, and time interval Δ T's opens
Time beginning and end time are gregorian calendar date；Customer order at least includes data below：Vegetable variety, supply of material date, confession
Goods quantity, quality standard, customer number.
Further, the pretreatment described in step S2 comprises the following steps：
The operation such as split or merged to customer order according to actual conditions, it is ensured that an order has：Unique vegetables
Kind, uniquely supply of material date, uniquely supply of material quantity, unique quality standard, unique customer number.
Retrieve all orders of the enterprise in sometime interval Δ T, and by supply of material date from the morning in order to
Evening is ranked up to order, the order list OrderList after being sorted.
Further, the validation verification described in step S2 comprises the following steps：
The non-null authentication of data：Whether proving time interval Δ T is more than 0, checking order list OrderList, vegetable variety
List VarietyList, kind production capacity list VarietyCapacityList, plantation code list RuleList, farm year
Facility area list FacilityList, labor cost information LaborCostList, input goods and materials cost information
Whether InputsCostList, kind precedence information VarietyRankList are empty.
Whether the vegetable variety in checking order list OrderList has farm production capacity arrangement in time interval Δ T.
Whether the vegetable variety in checking order list OrderList has corresponding plantation code.
Verify whether the supply of goods of all vegetable varieties in order is more than the maximum production capacity sum on all farms.
Further, the step S3 specifically includes following steps：
S31：Time interval Δ T is divided into the period that several natural numbers of days are t, Δ t is designated as1,Δt2,…,Δ
t|ΔT/t|, and in chronological sequence order handles the order in each period successively.Wherein, Δ T and t is positive integer, and t≤Δ
T, | Δ T/t | expression rounds up to Δ T/t.
S32：The supply of material date is filtered out in k-th of period Δ tkInterior all orders, based on order score function f (oi)
The comprehensive grading of the above order is calculated respectively, and order priority is sorted from high to low by comprehensive grading, generates period Δ
tkInterior order priority queue orderQueue, is designated as orderQueue=(o1,o2,…,oi...), wherein, order scoring
Function f (oi) be：
Wherein, oiRepresent the corresponding order of i-th of vegetable variety, piFor vegetable variety i anticipated price, yiFor vegetables product
Plant i per mu yield, amtiFor the vegetable variety i supply of goods, delayDaysiFor order oiThe supply of material date need postpone number of days, t
For period Δ tkInterior number of days, w1For client priority level (PRI) weight, w2For kind priority weighting, growDaysiFor vegetable variety
I crop cycle number of days, laboriFor the labor cost needed for planting vegetable kind i, inputsiFor planting vegetable kind i institutes
The input goods and materials cost needed, otheriFor other costs needed for planting vegetable kind i.
S33：The element in traversal queue orderQueue, takes out currentElement o successivelyi, according to order oiIn vegetables product
The conditional filterings such as kind, quality standard, farm kind production capacity, plantation protocol information, farm facilities information go out in period Δ tiIt is interior
All farms of the vegetable variety can be planted, fmQueue is designated asi=(fmi1,fmi2,…,fmin), wherein, n represents to meet bar
The farm quantity of part.If fmQueueiFor sky, then by order oiSupply of material date backward delay 1 day, and re-start farm sieve
Choosing, until fmQueueiIt is not sky.
S34：Based on genetic algorithm, order o is solvediOptimization Plant plane, to determine order oiPlantation on each farm
Area and implantation time, are formulated as：
J=ming (oi)
Constraints is：
akj≥0
ykj≥0
Wherein, oiThe corresponding order of i-th of vegetable variety is represented, J is solution order oiOptimize the target letter of Plant plane
Number, q (oi) it is order oiThe supply of goods, n be order oiCorresponding farm quantity, nkFor the number of idle greenhouse in k-th of farm
Amount, fkjRepresent order oiWhether j-th greenhouse on k-th farm, a are usedkjFor the area of j-th of greenhouse in k-th of farm,
ykjFor the per mu yield of j-th of greenhouse in k-th of farm, pkFor order oiThe anticipated price of middle vegetables, ckjFor jth in k-th of farm
The human cost of individual greenhouse and goods and materials cost, uckFor the unit distance cost of transportation of vegetables in k-th of farm, dkFor k-th of agriculture
Field and order oiThe distance of target customer, skCost, l are stored for the unit of vegetables in k-th of farmkjRepresent in k-th of farm
The economic benefit loss of unit area of j-th of greenhouse caused by continuously planting certain vegetables.
S35：Repeat step S33, S34, until the order in orderQueue all arranges to finish.
S36：Repeat step S32~S35, arranges next period Δ tk+1Interior order, by that analogy, until the time
The planting scheme scheduling of all orders in interval Δ T is finished, and generation time interval is the planting scheme schedule scheme under the conditions of t
plant, and by plantIt is added in feasible solution set R.
S37：Change t value, repeat step S31~S36 generates new planting scheme schedule scheme plant+1, and will
plant+1It is added in feasible solution set R.
S38：Feasible solution set R is traveled through, the economic well-being of workers and staff F (plan of each schedule scheme are calculatedt), therefrom select economical
The scheme of Income Maximum is used as optimal schedule scheme maxF (plant), wherein：
In formula, plantRepresent t kind schedule schemes, g (oi) it is order oiNet profit, m is total number of orders, and n is in t
Plant the quantity on farm needed for completing order scheduling under schedule scheme, niRepresent i-th of the agriculture used under t kind schedule schemes
The greenhouse number of field, ghijRepresent the area of j-th of greenhouse in i-th of farm, dayijRepresent in i-th of farm j-th greenhouse
Idle number of days, icijRepresent in i-th of farm the daily idle cost of unit area in j-th of greenhouse.
Further, methods described also includes visual presentation enterprise planting scheme scheduling result, specifically includes following step
Suddenly：
Utilize the vegetable cultivation information of two-dimensional table visual presentation each greenhouse in each farm in time interval Δ T
Dynamic change situation, the column direction of form is time dimension, is arranged from left to right in chronological order, for representing in some day
In all greenhouses occupancy situation.The line direction of form is greenhouse dimension, is arranged from top to bottom by farm, greenhouse number order,
The occupancy situation daily in time interval Δ T for representing some greenhouse.
The value of each cell in form is set to all cells in the numbering of correspondence order, traversal form, will
The background colour of the equal cell of all values is set to same color, and the background colour of the unequal cell of any two value is equal
It is different.
Compared with prior art, the present invention has advantages below：
The automatic scheduling method of vegetable cultivation plan provided by the present invention, consider vegetable variety type, farm production capacity,
The correlative factors such as land area, labor cost, goods and materials cost, transportation range build mathematical modeling, utilize intelligent optimization algorithm
Problem solving is carried out, it is determined that each farm needs vegetable variety, cultivated area and the implantation time planted.The method of the invention
Automation and the intelligent level of vegetable cultivation plan layout work can be effectively improved, the layout of planting scheme can be not only improved
Efficiency, reduces practitioner's labor intensity, and vegetable cultivation plan layout work can be made more to tend to be scientific and rationalize.
Brief description of the drawings
Fig. 1 is a kind of flow of large-scale vegetable cultivation enterprise planting scheme automatic generation method provided in an embodiment of the present invention
Schematic diagram；
Fig. 2 is the method flow diagram of progress pretreatment and validation verification in the embodiment of the present invention；
Fig. 3 is step S3 methods described flow charts of the embodiment of the present invention；
Fig. 4 is the schematic diagram that the embodiment of the present invention carries out visual presentation using two-dimensional table.
Embodiment
With reference to the accompanying drawings and examples, the embodiment to the present invention is described in further detail.Implement below
Example is used to illustrate the present invention, but is not limited to the scope of the present invention.
The large-scale vegetable cultivation enterprise that the present embodiment is related to refers to that the enterprise is distributed on diverse geographic location by several
Farm composition, be designated as fm1,fm2,...,fmn.Wherein, each farm is divided into several sections, is designated as disti.Each
Section is made up of several greenhouses again, is designated as ghj, greenhouse is the minimum plantation unit of enterprise.Each farm, section, greenhouse exist
Unique encodings are owned by enterprise-wide, section is encoded according to belonging to being obtained the coding of greenhouse, can be with according to section coding
Farm coding belonging to obtaining.
In production practices, for convenience of managing, farm is usually that certain vegetables sets a minimum cultivated area, in this reality
Apply in example, if greenhouse is minimum plantation unit, i.e., the cultivated area of every kind of vegetables is arranged in units of greenhouse, in synchronization one
Individual greenhouse can only plant a kind of vegetable variety.
A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method provided in an embodiment of the present invention, as shown in figure 1,
Comprise the following steps：
S1：Input data, carries out data initialization.
The data for inputting and being initialized include：Specify time interval Δ T, customer order list OrderList, vegetables
Kind list VarietyList, kind production capacity list VarietyCapacityList, plantation code list RuleList, farm
Annual facility area list FacilityList, labor cost information LaborCostList, goods and materials cost information
InputsCostList, kind precedence information VarietyRankList etc..
In practical application, vegetable cultivation enterprise carries out a vegetable cultivation plan layout, time interval Δ T usual every year
Time interval be usually a calendar year, i.e., since annual January 1, to end of day in December 31 then, and often
Individual consecutive days are minimum time unit.For example：The planting scheme in the year of layout 2016 is wanted, then time interval Δ T is from 2016 1
The moon starts on the 1st, to end of day December 31 in 2016.
The present embodiment be according to customer order demand carry out arrange vegetable cultivation plan, a customer order at least include with
Lower data item：Vegetable variety, supply of material date, supply of material quantity, quality standard, customer number.According to customer number, this can be inquired about
The information such as title, type, priority, the position of client.
S2：Data prediction and Validation of Data.
In order to reduce the complexity of algorithm, the operation efficiency and validity of algorithm are improved, before planting scheme scheduling is started,
Need first to pre-process input data and Validation of Data.Pretreatment and the flow chart of Validation of Data
As shown in Fig. 2 specifically including：
S21：The operation such as split or merged to customer order according to actual conditions, it is ensured that an order has：Uniquely
Vegetable variety, uniquely the supply of material date, uniquely the supply of material quantity, unique quality standard, unique customer number.
S22：All orders of the enterprise in time interval Δ T (i.e. a certain year) are retrieved, and by the confession in order
The goods date is from morning to night ranked up to order, the order list OrderList after being sorted.
S23：The non-null authentication of data, mainly includes：Whether proving time interval Δ T is more than 0, verifies order list
OrderList, vegetable variety list VarietyList, kind production capacity list VarietyCapacityList, plantation code row
Table RuleList, the annual facility area list FacilityList in farm, labor cost information LaborCostList, input
Whether goods and materials cost information InputsCostList, kind precedence information VarietyRankList etc. are empty.
S24:Whether the vegetable variety in checking order list OrderList has farm production capacity peace in time interval Δ T
Row.
S25:Whether the vegetable variety in checking order list OrderList has corresponding plantation code.
S26:Verify whether the supply of goods of all vegetable varieties in order is more than the maximum production capacity sum on all farms.
S3：Required according to customer order, using intelligent heuristics algorithm, during for all order arrangements plantation place and plantation
Between, generate enterprise's planting scheme scheduling result.
When vegetables enterprise arranges planting scheme, the constraint such as order demand, farm production capacity, usable land area should be considered
Condition, it is considered however that the shadow such as cost input, prospective earnings, logistics transportation cost, growth cycle, soil crop rotation of every kind of vegetables
Ring the factor of economic benefit.Problem solving is carried out using genetic algorithm, is that each order arranges suitable planting greenhouse and plantation
Time, on the premise of customer order requirement is met, the maximization of economic benefit of enterprise is made as far as possible.Method flow diagram such as Fig. 3
It is shown, concretely comprise the following steps：
S31：Certain annual Δ T is divided into the period that several number of days are t, Δ t is designated as1,Δt2,…,Δt|ΔT/t|,
And carry out the order scheduling of each period successively by the sequencing of above-mentioned each period, wherein, Δ T and t are positive integer and t
≤ΔT.Preferably, t initial value is 10, i.e., customer order scheduling is carried out in units of ten days.
S32：The order of each period is arranged successively, with k-th of period Δ tkExemplified by interior order scheduling, screen first
Go out to supply order of the date in the period, based on order score function f (oi) comprehensive grading of each order is calculated respectively, and
Order priority is sorted from high to low by comprehensive grading, period Δ t is generatediInterior order priority queue
OrderQueue, is designated as orderQueue=(o1,o2,…,oi...), wherein, order score function f (oi) be：
Wherein, oiRepresent the corresponding order of i-th of vegetable variety, piFor vegetable variety i anticipated price, yiFor vegetables product
Plant i per mu yield, amtiFor the vegetable variety i supply of goods, delayDaysiFor order oiThe supply of material date need postpone number of days, t
For period Δ tkInterior number of days, w1For client priority level (PRI) weight, w2For kind priority weighting, growDaysiFor vegetable variety
I crop cycle number of days, laboriFor the labor cost needed for planting vegetable kind i, inputsiFor planting vegetable kind i institutes
The input goods and materials cost needed, otheriFor other costs needed for planting vegetable kind i.
Preferably, client is more important, then its priority is higher, corresponding w1Value it is also bigger, according to client priority level (PRI)
It is descending to be divided into：Five ranks of A, B, C, D, E, corresponding weights are respectively：5、4、3、2、1.The priority of vegetable variety is got over
Height, then its corresponding w2Value it is bigger.w2Value be multiple fields expert carry out marking determination, by basis when expert is given a mark
The characteristics of experience, every kind of vegetables and its historic sales data are determined.If for example, certain vegetable variety is relatively easy kind
Plant, store and transport, added value is high, former years market sale is good, then its weighted value is bigger.
S33：The element in traversal queue orderQueue, takes out currentElement o successivelyi, according to order oiIn vegetables product
The conditional filterings such as kind, quality standard, farm kind production capacity, plantation protocol information, farm facilities information go out in period Δ tiIt is interior
All farms of the vegetable variety can be planted, fmQueue is designated asi=(fmi1,fmi2,…,fmin), wherein, n represents to meet bar
The farm quantity of part；If fmQueueiFor sky, then by order oiSupply of material date backward delay 1 day, and re-start farm sieve
Choosing, until fmQueueiIt is not sky.
S34：Based on genetic algorithm, order o is solvediOptimization Plant plane, to determine order oiPlantation on each farm
Area and implantation time, are formulated as：
J=ming (oi)
Constraints is：
akj≥0
ykj≥0
Wherein, J is solution order oiOptimize the object function of Plant plane, oiRepresent that i-th of vegetable variety is corresponding to order
It is single, q (oi) it is order oiThe supply of goods, n be order oiCorresponding farm quantity, nkFor the number of idle greenhouse in k-th of farm
Amount, fkjRepresent order oiWhether j-th greenhouse on k-th farm, a are usedkjFor the area of j-th of greenhouse in k-th of farm,
ykjFor the per mu yield of j-th of greenhouse in k-th of farm, pkFor order oiThe anticipated price of middle vegetables, ckjFor jth in k-th of farm
The human cost of individual greenhouse and goods and materials cost, uckFor the unit distance cost of transportation of vegetables in k-th of farm, dkFor k-th of agriculture
Field and order oiThe distance of target customer, skCost, l are stored for the unit of vegetables in k-th of farmkjRepresent in k-th of farm
The economic benefit loss of unit area of j-th of greenhouse caused by continuously planting certain vegetables.
Preferably, when carrying out problem solving using genetic algorithm, binary system is carried out to the idle greenhouse on all farms first
Coding, if order oiUsing j-th of greenhouse on k-th of farm, then fkj=1；Otherwise, fkj=0.Then, chromosome is carried out
After the operations such as selection, intersection and variation, the optimal solution gone wrong is calculated.And then, determine order oiBe arranged in which farm which
A little greenhouses are planted, and according to plantation code relevant information, determine the implantation time of vegetables, complete order oiScheduling.
S35：Repeat step S33, S34, until all orders in orderQueue all arrange to finish.
S36：Repeat step S32~35, arrange next period Δ tk+1Interior order, by that analogy, until time zone
Between the planting scheme schedulings of all orders in Δ T finish, generation time interval is the planting scheme schedule scheme under the conditions of t
plant, add it in feasible solution set R.
S37：Change t value, repeat step S31~36 generate new planting scheme schedule scheme plant+1, and added
Enter into feasible solution set R.
S38：Feasible solution set R is traveled through, the economic well-being of workers and staff F (plan of each schedule scheme are calculatedt), therefrom select economical
The scheme of Income Maximum is used as optimal schedule scheme maxF (plant), wherein：
In formula, plantRepresent t kind schedule schemes, g (oi) it is order oiNet profit, m is total number of orders, and n is in t
Plant the quantity on farm needed for completing order scheduling under schedule scheme, niRepresent i-th of the agriculture used under t kind schedule schemes
The greenhouse number of field, ghijRepresent the area of j-th of greenhouse in i-th of farm, dayijRepresent in i-th of farm j-th greenhouse
Idle number of days, icijRepresent in i-th of farm the daily idle cost of unit area in j-th of greenhouse.
Preferably, in order to improve operation efficiency, operand is reduced, t span can be carried out according to actual conditions
Limit, for example：t∈(3,5,7,10,…).According to F (plant) value it is descending, all schedule schemes are ranked up, and
Several schemes in the top are listed to select for user.
S4：Visual presentation enterprise planting scheme scheduling result.
Utilize the vegetable cultivation information of two-dimensional table visual presentation each greenhouse in each farm in time interval Δ T
Dynamic change situation, the column direction of form is time dimension, is arranged from left to right in chronological order, for representing in some day
In all greenhouses occupancy situation；The line direction of form is greenhouse dimension, is arranged from top to bottom by farm, greenhouse number order,
The occupancy situation daily in time interval Δ T for representing some greenhouse, as shown in Figure 4.
The value of each cell in form is set to all cells in the numbering of correspondence order, traversal form, will
The background colour of the equal cell of all values is set to same color, and the background colour of the unequal cell of any two value is equal
It is different.
Claims (5)
1. a kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method, it is characterised in that including：
S1：Input data, carries out data initialization；
S2：Input data in step S1 is pre-processed and validation verification；
S3：Required according to customer order, be that place and implantation time are planted in all order arrangements using intelligent heuristics algorithm, it is raw
Into enterprise's planting scheme scheduling result；
Input data described in step S1 includes：Specify time interval Δ T, customer order list OrderList, vegetable variety list
VarietyList, kind production capacity list VarietyCapacityList, plantation code list RuleList, the annual facility in farm
Area list FacilityList, labor cost information LaborCostList, goods and materials cost information InputsCostList,
Kind precedence information VarietyRankList；
Validation verification described in step S2 comprises the following steps：
The non-null authentication of data：Whether proving time interval Δ T is more than 0, checking order list OrderList, vegetable variety list
VarietyList, kind production capacity list VarietyCapacityList, plantation code list RuleList, the annual facility in farm
Area list FacilityList, labor cost information LaborCostList, input goods and materials cost information
Whether InputsCostList, kind precedence information VarietyRankList are empty；
Whether the vegetable variety in checking order list OrderList has farm production capacity arrangement in time interval Δ T；
Whether the vegetable variety in checking order list OrderList has corresponding plantation code；
Verify whether the supply of goods of all vegetable varieties in order is more than the maximum production capacity sum on all farms；
The step S3 specifically includes following steps：
S31：Time interval Δ T is divided into the period that several natural numbers of days are t, Δ t is designated as1,Δt2,…,Δt|ΔT/t|,
And in chronological sequence order handles the order in each period successively；Wherein, Δ T and t is positive integer, and t≤Δ T, | Δ T/
T | expression rounds up to Δ T/t；
S32：The supply of material date is filtered out in k-th of period Δ tkInterior all orders, based on order score function f (oi) respectively
The comprehensive grading of the above order is calculated, and order priority is sorted from high to low by comprehensive grading, period Δ t is generatedkIt is interior
Order priority queue orderQueue, be designated as orderQueue=(o1,o2,…,oi...), wherein, order score function f
(oi) be：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>o</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>*</mo>
<msub>
<mi>y</mi>
<mi>i</mi>
</msub>
<mo>*</mo>
<msub>
<mi>amt</mi>
<mi>i</mi>
</msub>
<mo>*</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>+</mo>
<msub>
<mi>delayDays</mi>
<mi>i</mi>
</msub>
<mo>/</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mo>*</mo>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
</mrow>
<mrow>
<msub>
<mi>growDays</mi>
<mi>i</mi>
</msub>
<mo>*</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>labor</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<msub>
<mi>inputs</mi>
<mi>i</mi>
</msub>
<mo>+</mo>
<msub>
<mi>other</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
</mrow>
Wherein, oiRepresent the corresponding order of i-th of vegetable variety, piFor vegetable variety i anticipated price, yiFor vegetable variety i's
Per mu yield, amtiFor the vegetable variety i supply of goods, delayDaysiFor order oiThe supply of material date need postpone number of days, when t is
Between section Δ tkInterior number of days, w1For client priority level (PRI) weight, w2For kind priority weighting, growDaysiFor vegetable variety i's
Crop cycle number of days, laboriFor the labor cost needed for planting vegetable kind i, inputsiFor needed for planting vegetable kind i
Input goods and materials cost, otheriFor other costs needed for planting vegetable kind i；
S33：The element in traversal queue orderQueue, takes out currentElement o successivelyi, according to order oiIn vegetable variety,
Quality standard, farm kind production capacity, plantation protocol information, farm facilities information conditional filtering go out in period Δ tiIt is interior to plant
All farms of the vegetable variety are planted, fmQueue is designated asi=(fmi1,fmi2,…,fmin), wherein, n represents qualified agriculture
Number；If fmQueueiFor sky, then by order oiSupply of material date backward delay 1 day, and re-start farm screening, directly
To fmQueueiIt is not sky；
S34：Based on genetic algorithm, order o is solvediOptimization Plant plane, to determine order oiCultivated area on each farm
With implantation time, it is formulated as：
J=ming (oi)
<mrow>
<mi>g</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>o</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>n</mi>
<mi>k</mi>
</msub>
</munderover>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>y</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>p</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msub>
<mi>c</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>uc</mi>
<mi>k</mi>
</msub>
<mo>*</mo>
<msub>
<mi>d</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msub>
<mi>s</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>l</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
</mrow>
Constraints is：
<mrow>
<mi>q</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>o</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>n</mi>
<mi>k</mi>
</msub>
</munderover>
<msub>
<mi>a</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>y</mi>
<mrow>
<mi>k</mi>
<mi>j</mi>
</mrow>
</msub>
</mrow>
akj≥0
ykj≥0
Wherein, oiThe corresponding order of i-th of vegetable variety is represented, J is solution order oiOptimize the object function of Plant plane, q
(oi) it is order oiThe supply of goods, n be order oiCorresponding farm quantity, nkFor the quantity of idle greenhouse in k-th of farm, fkj
Represent order oiWhether j-th greenhouse on k-th farm, a are usedkjFor the area of j-th of greenhouse in k-th of farm, ykjFor kth
The per mu yield of j-th of greenhouse, p in individual farmkFor order oiThe anticipated price of middle vegetables, ckjFor j-th greenhouse in k-th of farm
Human cost and goods and materials cost, uckFor the unit distance cost of transportation of vegetables in k-th of farm, dkFor k-th of farm and order
oiThe distance of target customer, skCost, l are stored for the unit of vegetables in k-th of farmkjRepresent j-th of greenhouse in k-th of farm
The economic benefit loss of unit area caused by continuously planting certain vegetables；
S35：Repeat step S33, S34, until the order in orderQueue all arranges to finish；
S36：Repeat step S32~S35, arranges next period Δ tk+1Interior order, the institute in time interval Δ T
The planting scheme scheduling for having order is finished, and generation time interval is the planting scheme schedule scheme plan under the conditions of tt, by plant
It is added in feasible solution set R；
S37：Change t value, repeat step S31~S36 generates new planting scheme schedule scheme plant+1, and by plant+1
It is added in feasible solution set R；
S38：Feasible solution set R is traveled through, the economic well-being of workers and staff F (plan of each schedule scheme are calculatedt), therefrom select economic well-being of workers and staff
Maximum scheme is used as optimal schedule scheme maxF (plant), wherein：
<mrow>
<mi>F</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>plan</mi>
<mi>t</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>m</mi>
</munderover>
<mi>g</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>o</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>n</mi>
<mi>i</mi>
</msub>
</munderover>
<msub>
<mi>gh</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>day</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>ic</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
</mrow>
In formula, plantRepresent t kind schedule schemes, g (oi) it is order oiNet profit, m is total number of orders, and n is in t kinds row
The quantity on farm, n needed for completing order scheduling under journey schemeiI-th of farm that expression has been used under t kind schedule schemes
Greenhouse number, ghijRepresent the area of j-th of greenhouse in i-th of farm, dayijRepresent the free time of j-th of greenhouse in i-th of farm
Number of days, icijRepresent in i-th of farm the daily idle cost of unit area in j-th of greenhouse.
2. large-scale vegetable cultivation enterprise planting scheme automatic generation method according to claim 1, it is characterised in that described
The farm that large-scale vegetable cultivation enterprise is distributed in by several on diverse geographic location is constituted, and is designated as fm1,fm2,...,fmn；Its
In, each farm is divided into several sections, is designated as disth；Each section is made up of several greenhouses again, is designated as ghj, greatly
Canopy is the minimum plantation unit of enterprise；Each farm, section, greenhouse are owned by unique encodings in enterprise-wide, according to greenhouse
Coding can obtain belonging to section coding, according to section coding can obtain belonging to farm encode.
3. large-scale vegetable cultivation enterprise planting scheme automatic generation method according to claim 1, it is characterised in that described
Time interval Δ T using consecutive days as least unit, at the beginning of time interval Δ T between and the end time be gregorian calendar date；Institute
Stating customer order at least includes data below：Vegetable variety, supply of material date, supply of material quantity, quality standard, customer number.
4. large-scale vegetable cultivation enterprise planting scheme automatic generation method according to claim 1, it is characterised in that step
Pretreatment described in S2 comprises the following steps：
Customer order is split according to actual conditions or union operation, it is ensured that an order has following feature：Have and only
There are a vegetable variety, uniquely supply of material date, uniquely supply of material quantity, unique quality standard, unique customer number；
All orders of the enterprise in sometime interval Δ T are retrieved, and it is from morning to night right by the supply of material date in order
Order is ranked up, the order list OrderList after being sorted.
5. large-scale vegetable cultivation enterprise planting scheme automatic generation method according to claim 1, it is characterised in that described
Method also includes visual presentation enterprise planting scheme scheduling result, specifically includes following steps：
Using two-dimensional table visual presentation in time interval Δ T in each farm the vegetable cultivation information of each greenhouse it is dynamic
State situation of change, the column direction of form is time dimension, is arranged from left to right in chronological order, for representing the institute in some day
There is the occupancy situation of greenhouse；The line direction of form is greenhouse dimension, arranges, is used for from top to bottom by farm, greenhouse number order
Represent some greenhouse occupancy situation daily in time interval Δ T；
The value of each cell in form is set to all cells in the numbering of correspondence order, traversal form, will be all
The background colour of the equal cell of value is set to same color, and any two is worth the background colour of unequal cell not
Together.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410855815.8A CN104573860B (en) | 2014-12-31 | 2014-12-31 | A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410855815.8A CN104573860B (en) | 2014-12-31 | 2014-12-31 | A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104573860A CN104573860A (en) | 2015-04-29 |
| CN104573860B true CN104573860B (en) | 2017-09-29 |
Family
ID=53089875
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410855815.8A Active CN104573860B (en) | 2014-12-31 | 2014-12-31 | A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104573860B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106408387A (en) * | 2016-09-23 | 2017-02-15 | 深圳前海弘稼科技有限公司 | Processing method and processing system for subscription information |
| CN108074162A (en) * | 2017-05-09 | 2018-05-25 | 重庆科技学院 | On-line off-line interaction platform based on bio-farm |
| CN108074128A (en) * | 2017-05-09 | 2018-05-25 | 重庆科技学院 | It gets a profit on line based on real farm computing platform |
| CN107832932A (en) * | 2017-10-31 | 2018-03-23 | 深圳春沐源控股有限公司 | A kind of Cultivate administration method and system |
| CN108985495B (en) * | 2018-06-26 | 2021-04-13 | 广州视源电子科技股份有限公司 | Material purchasing planning method and system |
| CN113163710B (en) * | 2018-10-24 | 2023-07-25 | 克莱米特有限责任公司 | System and method for identifying and utilizing test sites in an agricultural field |
| CN109948899A (en) * | 2019-02-11 | 2019-06-28 | 厦门邑通软件科技有限公司 | A kind of wisdom generation enterprise's production scheduling method and system |
| CN113763195A (en) * | 2020-08-21 | 2021-12-07 | 北京京东振世信息技术有限公司 | Planting plan control method and device and computer readable medium |
| CN113469831B (en) * | 2021-07-01 | 2024-06-14 | 浙江数秦科技有限公司 | Farming season navigation system based on block chain technology |
| CN114418783A (en) * | 2021-12-28 | 2022-04-29 | 北京市农林科学院信息技术研究中心 | Method, device and system for arranging crop breeding materials |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101320446A (en) * | 2008-02-25 | 2008-12-10 | 刘朋 | Development method for realizing agricultural science and technology, industrialization and order form |
| CN101477595A (en) * | 2009-01-22 | 2009-07-08 | 中国农业大学 | Regional crop type proportion planning system and method |
| CN103295159A (en) * | 2012-02-24 | 2013-09-11 | 鸿富锦精密工业（深圳）有限公司 | Agricultural product planting management control system and method |
| CN103295105A (en) * | 2013-06-20 | 2013-09-11 | 无锡百盛传感网络有限公司 | Regional agricultural multi-format management system for internet of things |
-
2014
- 2014-12-31 CN CN201410855815.8A patent/CN104573860B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101320446A (en) * | 2008-02-25 | 2008-12-10 | 刘朋 | Development method for realizing agricultural science and technology, industrialization and order form |
| CN101477595A (en) * | 2009-01-22 | 2009-07-08 | 中国农业大学 | Regional crop type proportion planning system and method |
| CN103295159A (en) * | 2012-02-24 | 2013-09-11 | 鸿富锦精密工业（深圳）有限公司 | Agricultural product planting management control system and method |
| CN103295105A (en) * | 2013-06-20 | 2013-09-11 | 无锡百盛传感网络有限公司 | Regional agricultural multi-format management system for internet of things |
Non-Patent Citations (1)
| Title |
|---|
| 鲜活农产品供应链的商业服务平台构建研究;桂群;《中国优秀硕士学位论文全文数据库》;20070215(第2期);正文第31-65页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104573860A (en) | 2015-04-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104573860B (en) | A kind of large-scale vegetable cultivation enterprise planting scheme automatic generation method | |
| Asgharipour et al. | Evaluation of the sustainability of four greenhouse vegetable production ecosystems based on an analysis of emergy and social characteristics” | |
| Brulard et al. | An integrated sizing and planning problem in designing diverse vegetable farming systems | |
| Caixeta-Filho et al. | Optimization of the production planning and trade of lily flowers at Jan de Wit Company | |
| Kharisma et al. | Linear programming model for vegetable crop rotation planning: a case study | |
| Aliano Filho et al. | An integrated multi-objective mathematical model for sugarcane harvesting considering cumulative degree-days | |
| Sholeh et al. | Analytical hierarchy process for land suitability analysis | |
| González-Gómez et al. | A model for cost calculation and management in a multiproduct agricultural framework. The case for ornamental plants | |
| Fikry et al. | A new mathematical model for the deterministic crop rotation planning problem | |
| Strapchuk | Integrated business model of sustainable development for agricultural sector | |
| Aghabalayev et al. | AZERBAIJAN’S SILK INDUSTRY DEVELOPMENT IN HISTORICAL PERSPECTIVE | |
| Sawangloke et al. | Measuring the labour productivity of sericultural farmers in Mahasarakham province, Thailand | |
| Cahn et al. | Irrigation and nitrogen management web-based software for lettuce production | |
| Rustambek | Forecast Indicators of the Provision of Population Demand Based on the Introduction of Innovative Technologies in Lemon Cultivation | |
| Peacock | Rural poverty and development in West Malaysia (1957-70) | |
| Nobre et al. | Integrating Nursery and Planting Activities | |
| Loman | Vertical Farming | |
| BELARMA | Assessing the Current Influence and Sustainability of the Kratky Hydroponics Method in Muntinlupa City | |
| Wahyudi et al. | Rural Potential, Food Security, and Poverty: A Study in Batu City, East Java | |
| Wahyudi et al. | Media Trend | |
| Meldoz et al. | Documentation and Promotion of Using Minisett Technique in Seed Yam Production | |
| AbdulRazak | Economics of date palm agriculture in the sultanate of Oman, current situation and future prospects | |
| Talawally et al. | Productivity of Rice Production: A Study of Ecowas Countries | |
| Salamanca et al. | Challenges and opportunities forsustainable economic growth inCachipay, Cundinamarca, basedon the characterization of itseconomic sectors and their impacton the local community | |
| Rogers et al. | Agricultural Employment and Migration in Northeast Thailand: Application of a Regional Planning Model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |