CN101702189A - Intelligent quick food preparation method - Google Patents
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- CN101702189A CN101702189A CN200910193556A CN200910193556A CN101702189A CN 101702189 A CN101702189 A CN 101702189A CN 200910193556 A CN200910193556 A CN 200910193556A CN 200910193556 A CN200910193556 A CN 200910193556A CN 101702189 A CN101702189 A CN 101702189A
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Abstract
The invention discloses an intelligent quick food preparation method comprising the following steps: dividing the people having dinner into N groups, determining the food preparation price of each group, and preparing food according to the following steps; randomly sequencing all the dishes; setting nutritional food preparation time limit T and food preparation program running time limit Tmax; operating a depth first search algorithm to generate first dish combination; judging the current time point, when the time point does not reach T, judging whether the dish combination simultaneously satisfies a first constraint condition and a second constraint condition, outputting the dish combination conforming to the conditions, and finishing food preparation, when the time point reaches T but does not reach Tmax, judging whether the dish combination satisfies the second constraint condition, outputting the dish combination conforming to the condition, and finishing food preparation; and when the time point reaches Tmax, choosing the dish combination in sequence from randomly sequenced dishes and outputting the dish combination. When outputting the dish combination which does not conform to the condition, the invention carries out adjustment by adopting the method of adjusting the constraint conditions. Compared with the prior art, the invention can quickly prepare the dishes with relatively rational nutrition collocation within reasonable time limit.
Description
Technical field
The present invention relates to the electric order dishes technical field of catering trade, particularly relate to a kind of intelligent quick food preparation method.
Background technology
Along with the raising of people's living standard and nutritional need, increasing people begin to pay attention to the problem of nutrition arrangement, thus nutrient diet are had higher requirement.
In the prior art, traditional nutrient diet mode is artificial pantry in the catering trade, artificial pantry needs waiter to learn each vegetable by heart, and know nutritional labeling and content thereof in each vegetable, also to understand the needs of human body simultaneously to heat energy, protein, mineral matter, vitamins and other nutritious components, and then select the collocation vegetable, carry out rational nutrient diet.The mode of this nutrient diet has proposed quite high requirement to waiter, needs just can satisfy the demands through strict training.When client provided the price of a desire consumption, waiter need take much time and piece together the vegetable combination, and the nutritional labeling evaluation of often vegetable of recommending being made up has subjectivity, the objective evaluation of shortage quantification.Moreover, especially under the situation many at number of meals, that the price of having a dinner is high, the artificial pantry inefficiency that just seems, and pantry is of low quality, can not estimate the nutritional labeling of vegetable objectively, this traditional nutrient diet mode can not satisfy the demand of current people to the nutrient laden of dietetic requirement, variation, rationalization.
Summary of the invention
Based on the deficiencies in the prior art, the problem that the present invention need solve is: a kind of intelligent quick food preparation method that can allot the relatively reasonable vegetable of nutrition arrangement in the rational time limit fast is provided.
For addressing the above problem, the invention provides a kind of intelligent quick food preparation method, it may further comprise the steps:
A, reception the number of meals and the price of having a dinner that the user imported;
B, described number of meals is divided into N group, obtain every group number of meals, and determine every group pantry price in described N the group, carry out pantry according to following steps respectively every group according to the price of having a dinner that the user imported, wherein, described N is the integer more than or equal to 1;
C, carry out randomly ordered to all vegetables in the database;
Be limited to T when D, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T;
E, to the vegetable after randomly ordered among the described step C, utilization depth-first search algorithm generates the combination of first vegetable;
F, judge current point in time, when described nutrient diet time limit T no show, execution in step G, when the described nutrient diet time limit, T arrived and during described pantry program run time limit Tmax no show, execution in step H, when described pantry program run time limit Tmax has arrived, execution in step I;
G, judge whether vegetable combination satisfies first constraint condition and second constraint condition simultaneously, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust first constraint condition and/or second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
H, judge whether vegetable combination satisfies second constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
Choose vegetable combination and output in I, the vegetable from described step C after randomly ordered in order;
Wherein, described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows.
In addition, nutritional labeling comprises heat, moisture, protein, fat, carbohydrate, cellulose, carrotene, VA equivalent, retinol equivalent, vitamin B1, vitamin B2, nicotinic acid, vitamin E, cholesterol, potassium, sodium, calcium, magnesium, iron, manganese, zinc, copper, phosphorus, selenium, carbohydrates etc., and described nutritional labeling can choose a kind of in the above nutritional labeling as required or more than one are as constraint condition.
Further, further comprise step J after the described steps A: if receive the user the described vegetable of exporting is made up unsatisfied information, then return steps A and carry out pantry again.
Further, at further comprising the steps of B0 between described steps A and the step B: judge in the reasonable price interval whether the price of having a dinner that the user imports presetting, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported.
Further, described step B0 specifically comprises:
The price summation of all vegetables in B01, the computational data storehouse, the price summation of all vegetables in the database that calculates is labeled as SUM, seek cheapest vegetable in all vegetables in described database, and be MIN the price tags of described cheapest vegetable;
B02, described reasonable price interval of presetting are [MIN, SUM];
B03, judge that whether the price of having a dinner that the user imports is at [MIN, SUM] in, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported, the method of the described adjustment price of having a dinner that the user imported is: if receive the information of price greater than SUM of having a dinner that the user imports, be SUM then with the price adjustment of having a dinner that the user imported, if the price of having a dinner that receives that the user imports is MIN with the price adjustment of having a dinner that the user imported then less than the information of MIN.
Further, at further comprising the steps of B00 between described step B0 and the step B: judge obtain by step B0 have a dinner price whether in the reasonable fluctuation range of consumption valency, if, the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported.
Further, described step B00 specifically comprises:
B001, according to the number of meals that the user imported, calculate the number scope [a, b] of required pantry vegetable;
B002, according to the number scope of required pantry vegetable, calculate the ceiling price of required pantry vegetable and the floor price of required pantry vegetable, wherein, the computing method of the ceiling price of required pantry vegetable are: the price summation sum_max of b the vegetable that price is the highest in all vegetables, and the computing method of the floor price of required pantry vegetable are: the price summation sum_min of a cheapest a vegetable in all vegetables;
The reasonable fluctuation range of B003, the described consumption valency of calculating:
B003.1, according to the historical consume database of record that presets, calculate the average price and the historical pre-capita consumption volume of all vegetables;
B003.2, setting reference price are standard=Max (average price of all vegetables, historical pre-capita consumption volume), and wherein, Max is for getting max function;
The reasonable fluctuation range of B003.3, the described consumption valency of calculating is: [Max (standard* number of meals * 0.6, sum_min), Min (standard* number of meals/0.6, sum_max)], wherein, Max is for getting max function, and Min is for getting minimum value function;
B004, judge by what step B0 obtained and have a dinner price whether in the reasonable fluctuation range of described consumption valency, if the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported, wherein, the method for the described adjustment number of meals that the user imported is: adjusted number of meals is the ratio of have a dinner price and the described reference price obtained by step B0.This ratio is through rounding processing.
Further, before described step C, also comprise: according to the historical consume database of record that presets, obtain the classification of each vegetable in all vegetables, and the composition of the vegetable of each classification, the random number of demarcating between the 0-100 is corresponding with each classification of vegetable;
Adopt the depth-first search algorithm in the described step e, generate in the process of vegetable combination in the vegetable from described step C after randomly ordered, utilize the method for the random number between the 0-100 that generates at random, determine the affiliated classification of vegetable of next step searching, make in seeking the result, allow the classification difference under adjacent arbitrarily two vegetables in the vegetable combination that generates as far as possible.
Further, the computing method of the evaluation of nutrition score value summation of the nutritional labeling of the described vegetable combination in described first constraint condition are: the evaluation of nutrition score value that calculates each nutritional labeling respectively is that (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the described vegetable combination/every group to 100*Min, 1/ (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the combination of described vegetable/every group)), the evaluation of nutrition score value addition of each nutritional labeling that described vegetable is made up is the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination again, wherein, described every per capita meal-trade is formed branch ingestion standard amount for setting in advance;
The computing method of the fluctuation range that every group pantry price in described second constraint condition allows are:
Described every group pantry price is number of meals/described number of meals of described every group of the price * of having a dinner;
The fluctuation range that described every group pantry price allows is [every group pantry price * (1-10%), every group pantry price/(1-10%)].
In addition, the fluctuation range of described permission can also be for fluctuating 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% etc. up and down on the basis of described every assembly meal price.
Further, the method for adjusting first constraint condition among the described step G is for reducing first threshold, and the method for adjusting second constraint condition is for the upper limit of the fluctuation range of the described permission of raising or enlarge the upper and lower bound of the fluctuation range of described permission simultaneously,
The method of adjusting second constraint condition among the described step H is for the upper limit of the fluctuation range that improves described permission or enlarge the upper and lower bound of the fluctuation range of described permission simultaneously.
The present invention also provides a kind of intelligent quick food preparation method, and it may further comprise the steps:
A, reception the number of meals and the price of having a dinner that the user imported;
B, described number of meals is divided into N group, obtain every group number of meals, and determine every group pantry price in described N the group, carry out pantry according to following steps respectively every group according to the price of having a dinner that the user imported, wherein, described N is the integer more than or equal to 1;
C, carry out randomly ordered to all vegetables in the database;
Be limited to T when D, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T;
E, to the vegetable after randomly ordered among the described step C, utilization depth-first search algorithm generates the combination of first vegetable;
F, judge current point in time, when described nutrient diet time limit T no show, execution in step G, when the described nutrient diet time limit, T arrived and during described pantry program run time limit Tmax no show, execution in step H, when described pantry program run time limit Tmax has arrived, execution in step I;
G, judge whether vegetable combination satisfies first constraint condition, second constraint condition and the 3rd constraint condition simultaneously, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust first constraint condition and/or second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
H, judge whether vegetable combination satisfies second constraint condition and the 3rd constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
Choose vegetable combination and output in I, the vegetable from described step C after randomly ordered in order; Wherein, described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows.
Described the 3rd constraint condition is: the absolute value of the potential of hydrogen data addition summation of vegetable is less than second threshold value in the described vegetable combination, and wherein, the potential of hydrogen data of vegetable are for setting in advance in the described vegetable combination.
The present invention is divided into N group with number of meals, and determines every group pantry price according to the price of having a dinner that the user imported, and carries out pantry according to following steps respectively to every group; Carry out randomly ordered to all vegetables in the database; Be limited to T when setting nutrient diet, be limited to Tmax when setting the pantry program run; To the vegetable after randomly ordered among the described step C, utilization depth-first search algorithm generates the combination of first vegetable; Judge current point in time, when described nutrient diet time limit T no show, judge vegetable combination whether satisfied simultaneously first constraint condition and second constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust first constraint condition and/or second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F; When the described nutrient diet time limit, T arrived and during described pantry program run time limit Tmax no show, judge whether the vegetable combination satisfies second constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F; When described pantry program run time limit Tmax has arrived, choose vegetable combination and output the vegetable after randomly ordered in order.Wherein, described first constraint condition be the evaluation of nutrition score value summation of nutritional labeling of vegetable combination greater than the first threshold of setting, second constraint condition is that the price of vegetable combination drops in the fluctuation range that every group pantry price allows.Compared with prior art, the present invention can reasonably allot the relatively reasonable vegetable combination of nutrition arrangement in the time limit fast.And the invention solves especially many at number of meals and situation that the price of having a dinner is high under carry out the problem of nutrient diet, be implemented in and generate the relatively reasonable vegetable combination of nutrition arrangement in the rational time fast thereby adopted grouping to divide respectively the method for pantry.The present invention also at the number of meals of the user's input that occurs in the practical application and the irrational situation of price extreme of having a dinner per capita, has proposed feasible adjustment scheme.
Description of drawings
The invention will be further described to utilize accompanying drawing, but the embodiment in the accompanying drawing does not constitute any limitation of the invention.
Fig. 1 is a kind of intelligent quick food preparation method of the present invention method flow diagram in a preferred embodiment;
Fig. 2 is a kind of intelligent quick food preparation method of the present invention method flow diagram in a further advantageous embodiment.
Embodiment
With the following Examples the present invention is further described:
Embodiment one:
The embodiment one of a kind of intelligent quick food preparation method of the present invention is a kind of method flow diagram of the present invention as shown in Figure 1.
Concrete, a kind of intelligent quick food preparation method, it may further comprise the steps:
(1) the minimum number of the each pantry of setting is N0 (wherein, N0＞0), and the current pantry number for the treatment of of initial setting is the number of meals that described user imported;
(2) judge whether the current pantry number for the treatment of is 0, if then finish pantry; Otherwise, execution in step E04;
(3) if the current pantry number for the treatment of more than or equal to N0*2, then setting this time pantry number is N0; If the current pantry number for the treatment of is less than N0*2, then setting this time pantry number is the current pantry number for the treatment of;
(4) calculate and to treat pantry number=current pantry number-this time pantry number for the treatment of next time;
(5) return step (2).Circulation successively is until the pantry of finishing all numbers of meals.
The method of described division grouping can also be in advance number of meals to be divided grouping by every group of different number of meals.
Be limited to T when step 104, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T; Set nutrient diet time limit and pantry program run time limit, be long for fear of period of reservation of number, finish pantry in the nutrient diet time limit that can be scheduled to again and pantry program run time limit, if and fully take into account and when setting nutrient diet, be limited to the solution separately that to finish pantry in the T, enlarge and set nutrient diet time limit T, set pantry program run time limit Tmax, prolong and wait for the time limit, assurance can be finished pantry work.The setting in this nutrient diet time limit and pantry program run time limit can be set according to the stand-by period that people's psychology is generally speaking accepted.The time limit here also can be to be set at a time limit, and three time limits or three take all factors into consideration various situations more than the time limit, are limited to more preferably scheme in the time of two.
In addition, wherein the number of vegetable can be calculated according to the number of meals that the user imported in this vegetable combination, if after the grouping with the time every group number of meals, suppose that the number of meals that the user imports is (or number of meals of every group) L, then the number of vegetable can also be a scope [a for L or L+1 or L+2 etc. in the vegetable combination, b], a=N-1 wherein, b=N+2 can also be other scope.
Choose vegetable combination and output in step 109, the vegetable from described step 103 after randomly ordered in order.The account form of the number of vegetable is the same in this vegetable combination.
Wherein, described constraint condition comprises first constraint condition and second constraint condition,
Described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
In addition, nutritional labeling comprises heat, moisture, protein, fat, carbohydrate, cellulose, carrotene, VA equivalent, retinol equivalent, vitamin B1, vitamin B2, nicotinic acid, vitamin E, cholesterol, potassium, sodium, calcium, magnesium, iron, manganese, zinc, copper, phosphorus, selenium, carbohydrates etc., and described nutritional labeling can choose a kind of in the above nutritional labeling as required or more than one are as constraint condition.
From the above nutritional labeling of enumerating, choose, for example choose three kinds of protein, fat and heats, the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting, and the evaluation of nutrition score value summation of protein, fat and heat that is described vegetable combination is greater than the first threshold of setting.
Described first threshold can calculate ScoreGate=(number of 1.0-a* number of meals/vegetable combination) * S in order to following method; Wherein, S is artificial the setting, the evaluation of nutrition score value full marks of setting every kind of nutritional labeling of vegetable are 100 minutes, if think the evaluation of nutrition score value of every kind of nutritional labeling be 80 minutes promptly satisfied, then the full marks of protein, fat and three kinds of evaluation of nutrition score values of heat are 300 minutes, and the S here is 240; If think the evaluation of nutrition score value of every kind of nutritional labeling be 90 minutes promptly satisfied, then the full marks of protein, fat and three kinds of evaluation of nutrition score values of heat are 300 minutes, the S here is 270; Choosing of S can be adjusted as required.Moreover wherein, a is a coefficient, and this coefficient a is a positive number, and the expression number of meals is many more, and threshold value is more little.A chooses 1 in the preferred scheme.
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows; Set fluctuation range and be in order to enlarge this fluctuation range when pantry fail, thereby realize the purpose of successful pantry, the fluctuation range maximal value of this permission can not be above 40%.
The whole thinking of pantry is if in rational nutrient diet time limit T, generating a vegetable combination according to the depth-first search algorithm just judges once, if find the vegetable combination of satisfying first constraint condition and second constraint condition simultaneously, then finish pantry, export this vegetable combination; If all vegetable combinations that generate according to the depth-first search algorithm all have been judged, in the time of all can't finding the vegetable combination of satisfying first constraint condition and second constraint condition simultaneously, and nutrient diet time limit T does not also arrive at this moment, preferential first constraint condition of adjusting, again make up from generating first vegetable according to the depth-first search algorithm, generating a vegetable combination just judges once, if all vegetable combinations that generate according to the depth-first search algorithm all have been judged, when making up according to the vegetable that also can't find satisfied simultaneously first constraint condition and second constraint condition after first constraint condition after adjusting, then adjusting second constraint condition seeks to separate, the same, arrive until nutrient diet time limit T; When the nutrient diet time limit, T arrived, then abandoning the constraint of first constraint condition searches for, if during the pantry program run time limit Tmax no show of this moment, then judge according to the vegetable combination that above-mentioned continuation generates, if all vegetable combinations that generate according to the depth-first search algorithm all have been judged, still can't find when satisfying the separating of second constraint condition, adjust second constraint condition, again make up from generating first vegetable according to the depth-first search algorithm, generate a vegetable combination and just judge once, arrive until pantry program run time limit Tmax; If pantry program run time limit Tmax arrives, reasonably separate and still can not find, then at random and also unduplicated vegetable randomly ordered from step 103 in choose vegetable combination and output in order, finally finish pantry.
Concrete, further comprise step 110 after the described step 101: if receive the user the described vegetable of exporting is made up unsatisfied information, then return step 101 and carry out pantry again.Intelligent quick food preparation method of the present invention is dynamically to recommend, and for same constraint condition, each to carry out the institute's vegetable that produces combination all be different, so if the vegetable of current generation is made up when being unsatisfied with as the user, can restart to search for.
Concrete, between described step 101 and the step 102 further comprising the steps of 200: judge in the reasonable price interval whether the price of having a dinner that the user imports presetting, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported.Setting step 200 is to consider the extremely irrational situation of price of having a dinner that might occur user's input in the practical application, be far longer than the price summation of all vegetables in the database such as the price of having a dinner of user's input, in this case, even vegetable output all in the database is not satisfied yet user's demand, the price of having a dinner of user's input is less than cheapest vegetable in the database for another example, in this case, even cheapest vegetable in the database is exported the demand that does not also satisfy the user, the scheme that the irrational price of having a dinner of extreme that has proposed that thus the user is imported is adjusted.
Concrete, described step 200 specifically comprises:
The price summation of all vegetables in step 201, the computational data storehouse, the price summation of all vegetables in the database that calculates is labeled as SUM, seek cheapest vegetable in all vegetables in described database, and be MIN the price tags of described cheapest vegetable;
Step 202, described reasonable price interval of presetting are [MIN, SUM];
Step 203, judge that whether the price of having a dinner that the user imports is at [MIN, SUM] in, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported, the method of the described adjustment price of having a dinner that the user imported is: if receive the information of price greater than SUM of having a dinner that the user imports, be SUM then with the price adjustment of having a dinner that the user imported, if the price of having a dinner that receives that the user imports is MIN with the price adjustment of having a dinner that the user imported then less than the information of MIN.
Above step 200 only is most preferred scheme, the method that can also comprise other, such as: can artificially set a relatively reasonable range, if the price of having a dinner of user's input surpasses the upper limit of this zone of reasonableness, then the price adjustment of having a dinner with user's input is the upper limit of this scope, if the price of having a dinner of user's input is lower than the lower limit of this scope, then the price adjustment of having a dinner with user's input is the lower limit of this scope.
Concrete, between described step 200 and the step 102 further comprising the steps of 300: judge obtain by described step 200 have a dinner price whether in the reasonable fluctuation range of consumption valency, if, the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported.Setting step 300 is to consider extremely irrational situation of the proportioning of the have a dinner price and the number of meals that might occur user's input in the practical application and the price of having a dinner per capita, the scheme that the number of meals that has proposed that thus the user is imported is adjusted.
Concrete, described step 300 specifically comprises:
Step 301, according to the number of meals that the user imported, the number scope of calculating required pantry vegetable is [a, b]; Wherein, a is N-1, and b is N+2, and the number scope of this pantry vegetable can also be other computing method, is N-1 such as a, and b is N+1; A is N-2, and b is N+2; A is N-2, and b is N+3, can also be other forms of computing method or the like.
Step 302, according to the number scope of required pantry vegetable, calculate the ceiling price of required pantry vegetable and the floor price of required pantry vegetable, wherein, the computing method of the ceiling price of required pantry vegetable are: the price summation sum_max of b the vegetable that price is the highest in all vegetables, and the computing method of the floor price of required pantry vegetable are: the price summation sum_min of a cheapest a vegetable in all vegetables;
The reasonable fluctuation range of step 303, the described consumption valency of calculating:
Step 303.1, according to the historical consume database of record that presets, calculate the average price and the historical pre-capita consumption volume of all vegetables;
Step 303.2, setting reference price are standard=Max (average price of all vegetables, historical pre-capita consumption volume), and wherein, Max is for getting max function;
The reasonable fluctuation range of step 303.3, the described consumption valency of calculating is: [Max (standard* number of meals * 0.6, sum_min), Min (standard* number of meals/0.6, sum_max)], wherein, Max is for getting max function, and Min is for getting minimum value function;
Step 304, judge by what step 200 was obtained and have a dinner price whether in the reasonable fluctuation range of described consumption valency, if the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported, wherein, the method for the described adjustment number of meals that the user imported is: adjusted number of meals is the ratio of have a dinner price and the described reference price obtained by step 200.This ratio is through rounding processing.
Concrete, before described step 103, also comprise: according to the historical consume database of record that presets, obtain the classification of each vegetable in all vegetables, and the composition of the vegetable of each classification, the random number of demarcating between the 0-100 is corresponding with each classification of vegetable;
Employing depth-first search algorithm in the described step 105, generate in the process of vegetable combination in the vegetable from described step 103 after randomly ordered, utilize the method for the random number between the 0-100 that generates at random, determine the affiliated classification of vegetable of next step searching, make in seeking the result, allow the classification difference under adjacent arbitrarily two vegetables in each vegetable combination in the vegetable combination of sets that generates as far as possible.
Illustrate: according to the historical consume database of record, for each vegetable in all vegetables is set classification, can be divided into seafood, meat, three classifications of greengrocery, obtain the composition of the vegetable of each classification, suppose in the historical consume database of record, find that 30% is seafood, 40% is meat, and 30% is vegetables.
Generate random number: rand (rand is less than 100 integer greater than 0)
Can stipulate: between 0 to 30, the target dish class of current search is a seafood as if rand, if between 30 to 70, the target dish class of search is a meat, if between 70 to 100, the target dish class of search is a greengrocery.
The depth-first search algorithm at first will be set up following digraph.Each vegetable in all vegetables all is abstracted into a summit in the digraph.For any two vegetables in all vegetables, if, the numbering of vegetable a is greater than the numbering of vegetable b, and the classification under the vegetable a is different with classification under the vegetable b, then from summit that vegetable a is abstracted into to directed edge of summit connection that vegetable b is abstracted into.
The detailed process of depth-first search algorithm is: establishing x is current accessed summit, after x was done access flag, select a limit of not detecting from x (x, y).If find that summit y visited, then reselect another limit of not detecting, otherwise (x y) arrives the y that had not visited, and is labeled as to the y visit and with it and visits along the limit from x; Begin search from y then,, promptly visited all after the summit that y can reach, just date back to summit x, and select a limit of not detecting again from x up to all paths of having searched for from y.Said process was till all having detected from all limits of x.At this moment, if x is not a source point, then date back to the summit of accessed mistake before x; Otherwise all and source point have all accessed mistake in the summit that the path communicates (promptly from all summits that source point can reach) among the figure, if figure G is a connected graph, then ergodic process finishes, otherwise continues to select not accessed as yet summit as new source point, carries out new search procedure.
Concrete, the computing method of the evaluation of nutrition score value summation of the nutritional labeling of the described vegetable combination in described first constraint condition are: the evaluation of nutrition score value that calculates each nutritional labeling respectively is that (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the described vegetable combination/every group to 100*Min, 1/ (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the combination of described vegetable/every group)), the evaluation of nutrition score value addition of each nutritional labeling that described vegetable is made up is the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination again, wherein, described every per capita meal-trade is formed branch ingestion standard amount for setting in advance;
From the above nutritional labeling of enumerating, choose, for example choose three kinds of protein, fat and heats, the evaluation of nutrition score value Score (Protein) that calculates the protein of all vegetables combination is: 100*Min (number of meals/every per capita meal protein ingestion standard amount of the total protein in the described vegetable combination/every group, 1/ (total protein in the described vegetable combination/every group number of meals/every per capita meal protein ingestion standard amount)); The evaluation of nutrition score value Score (Fat) that calculates the fat of all vegetables combination is: 100*Min (number of meals/fatty ingestion standard amount of every per capita meal of the amount of total fat in the described vegetable combination/every group, 1/ (amount of total fat in the described vegetable combination/every group number of meals/fatty ingestion standard amount of every per capita meal)); The evaluation of nutrition score value Score (Heat) that calculates the heat of all vegetables combination is: 100*Min (number of meals/every per capita meal heat ingestion standard amount of the heat total amount in the described vegetable combination/every group, 1/ (the heat total amount in the described vegetable combination/every group number of meals/every per capita meal heat ingestion standard amount)); Evaluation of nutrition score value Score (Heat) addition of the evaluation of nutrition score value Score (Fat) of the evaluation of nutrition score value Score (Protein) of the protein that described vegetable is made up, fat, heat is the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination again.
The computing method of the fluctuation range that every group pantry price in described second constraint condition allows are:
Have a dinner number of meals/described number of meals of every group of price * of described every group pantry price=described;
The fluctuation range that described every group pantry price allows is [every group pantry price * (1-10%), every group pantry price/(1-10%)].
In addition, more than calculating the fluctuation range that allows only is a kind of computing method, can also be [every group pantry price * (1-10%), every group pantry price * (1+10%)] for the fluctuation range that allows.
The fluctuation range of described permission can also be for fluctuating 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% etc. or arbitrary value within 40% up and down on the basis of described every assembly meal price.
Embodiment two:
The embodiment two of a kind of intelligent quick food preparation method of the present invention is another kind of method flow diagram of the present invention as shown in Figure 2.
Concrete, a kind of intelligent quick food preparation method, it can also may further comprise the steps:
(1) the minimum number of the each pantry of setting is N0 (wherein, N0＞0), and the current pantry number for the treatment of of initial setting is the number of meals that described user imported;
(2) judge whether the current pantry number for the treatment of is 0, if then finish pantry; Otherwise, execution in step E04;
(3) if the current pantry number for the treatment of more than or equal to N0*2, then setting this time pantry number is N0; If the current pantry number for the treatment of is less than N0*2, then setting this time pantry number is the current pantry number for the treatment of;
(4) calculate and to treat pantry number=current pantry number-this time pantry number for the treatment of next time;
(5) return step (2).Circulation successively is until the pantry of finishing all numbers of meals.
The method of described division grouping can also be in advance number of meals to be divided grouping by every group of different number of meals.
Be limited to T when step 104, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T; Set nutrient diet time limit and pantry program run time limit, be long for fear of period of reservation of number, finish pantry in the nutrient diet time limit that can be scheduled to again and pantry program run time limit, if and fully take into account and when setting nutrient diet, be limited to the solution separately that to finish pantry in the T, enlarge and set nutrient diet time limit T, set pantry program run time limit Tmax, prolong and wait for the time limit, assurance can be finished pantry work.The setting in this nutrient diet time limit and pantry program run time limit can be set according to the stand-by period that people's psychology is generally speaking accepted.The time limit here also can be to be set at a time limit, and three time limits or three take all factors into consideration various situations more than the time limit, are limited to more preferably scheme in the time of two.
In addition, wherein the number of vegetable can be calculated according to the number of meals that the user imported in this vegetable combination, if after the grouping with the time every group number of meals, suppose that the number of meals that the user imports is (or number of meals of every group) L, then the number of vegetable can also be a scope [a for L or L+1 or L+2 etc. in the vegetable combination, b], a=N-1 wherein, b=N+2 can also be other scope.
Choose vegetable combination and output in step 109, the vegetable from described step 103 after randomly ordered in order.The computing method of the number of vegetable are the same in this vegetable combination.
Wherein,
Described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
In addition, nutritional labeling comprises heat, moisture, protein, fat, carbohydrate, cellulose, carrotene, VA equivalent, retinol equivalent, vitamin B1, vitamin B2, nicotinic acid, vitamin E, cholesterol, potassium, sodium, calcium, magnesium, iron, manganese, zinc, copper, phosphorus, selenium, carbohydrates etc., and described nutritional labeling can choose a kind of in the above nutritional labeling as required or more than one are as constraint condition.
From the above nutritional labeling of enumerating, choose, for example choose three kinds of protein, fat and heats, the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting, and the evaluation of nutrition score value summation of protein, fat and heat that is described vegetable combination is greater than the first threshold of setting.
Described first threshold can calculate ScoreGate=(number of 1.0-a* number of meals/vegetable combination) * S in order to following method; Wherein, S is artificial the setting, the evaluation of nutrition score value full marks of setting every kind of nutritional labeling of vegetable are 100 minutes, if think the evaluation of nutrition score value of every kind of nutritional labeling be 80 minutes promptly satisfied, then the full marks of protein, fat and three kinds of evaluation of nutrition score values of heat are 300 minutes, and the S here is 240; If think the evaluation of nutrition score value of every kind of nutritional labeling be 90 minutes promptly satisfied, then the full marks of protein, fat and three kinds of evaluation of nutrition score values of heat are 300 minutes, the S here is 270; Choosing of S can be adjusted as required.Moreover wherein, a is a coefficient, and this coefficient a is a positive number, and the expression number of meals is many more, and threshold value is more little.A chooses 1 in the preferred scheme.
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows; Set fluctuation range and be in order to enlarge this fluctuation range when pantry fail, thereby realize the purpose of successful pantry, the fluctuation range maximal value of this permission can not be above 40%.
Described the 3rd constraint condition is: the absolute value of the potential of hydrogen data addition summation of vegetable is less than second threshold value in the described vegetable combination, and wherein, the potential of hydrogen data of vegetable are for setting in advance in the described vegetable combination.The concrete potential of hydrogen data storage method of vegetable in database is:
If vegetable is a highly acid, the potential of hydrogen of obtaining from database is-2;
If vegetable is acid, the potential of hydrogen of obtaining from database is-1;
If vegetable is neutral, the potential of hydrogen of obtaining from database is 0;
If vegetable is an alkalescence, the potential of hydrogen of obtaining from database is 1;
If vegetable is a highly acid, the potential of hydrogen of obtaining from database is 2;
Less than second threshold value, the definite of this second threshold value can preestablish according to concrete needs.
The whole thinking of pantry is if in rational nutrient diet time limit T, generating a vegetable combination according to the depth-first search algorithm just judges once, if find the vegetable combination of satisfying first constraint condition, second constraint condition and the 3rd constraint condition simultaneously, then finish pantry, export this vegetable combination; If all vegetable combinations that generate according to the depth-first search algorithm all have been judged, all can't find and satisfy first constraint condition simultaneously, when the vegetable of second constraint condition and the 3rd constraint condition makes up, and nutrient diet time limit T does not also arrive at this moment, preferential first constraint condition of adjusting, again make up from generating first vegetable according to the depth-first search algorithm, generating a vegetable combination just judges once, if all vegetable combinations that generate according to the depth-first search algorithm all have been judged, after adjusting back first constraint condition, also can't find satisfied simultaneously first constraint condition, when the vegetable of second constraint condition and the 3rd constraint condition makes up, then adjusting second constraint condition seeks to separate, the same, arrive until nutrient diet time limit T; When the nutrient diet time limit, T arrived, then abandoning the constraint of first constraint condition searches for, if during the pantry program run time limit Tmax no show of this moment, then judge according to the vegetable combination that above-mentioned continuation generates, if all vegetable combinations that generate according to the depth-first search algorithm all have been judged, still can't find when satisfying the separating of second constraint condition and the 3rd constraint condition, adjust second constraint condition, again make up from generating first vegetable according to the depth-first search algorithm, generate a vegetable combination and just judge once, arrive until pantry program run time limit Tmax; If pantry program run time limit Tmax arrives, reasonably separate and still can not find, then at random and also unduplicated vegetable randomly ordered from step 103 in choose vegetable combination and output in order, finally finish pantry.
The present invention can be applied in the intelligent quick food preparation of vegetable, the intellectuality of commodity purchases by group on the relevant field such as the method various and of the present invention of recommending purchase fast.
Should be noted that at last; above embodiment is only in order to illustrate technical scheme of the present invention; but not limiting the scope of the invention; although the present invention has been done to explain with reference to preferred embodiment; those of ordinary skill in the art is to be understood that; can make amendment or be equal to replacement technical scheme of the present invention, and not break away from the essence and the scope of technical solution of the present invention.
Claims (10)
1. an intelligent quick food preparation method is characterized in that, may further comprise the steps:
A, reception the number of meals and the price of having a dinner that the user imported;
B, described number of meals is divided into N group, obtain every group number of meals, and determine every group pantry price in described N the group, carry out pantry according to following steps respectively every group according to the price of having a dinner that the user imported, wherein, described N is the integer more than or equal to 1;
C, carry out randomly ordered to all vegetables in the database;
Be limited to T when D, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T;
E, to the vegetable after randomly ordered among the described step C, utilization depth-first search algorithm generates the combination of first vegetable;
F, judge current point in time, when described nutrient diet time limit T no show, execution in step G, when the described nutrient diet time limit, T arrived and during described pantry program run time limit Tmax no show, execution in step H, when described pantry program run time limit Tmax has arrived, execution in step I;
G, judge whether vegetable combination satisfies first constraint condition and second constraint condition simultaneously, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust first constraint condition and/or second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
H, judge whether vegetable combination satisfies second constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
Choose vegetable combination and output in I, the vegetable from described step C after randomly ordered in order;
Wherein, described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows.
2. intelligent quick food preparation method according to claim 1 is characterized in that, further comprises step J after the described steps A: if receive the user the described vegetable of exporting is made up unsatisfied information, then return steps A and carry out pantry again.
3. intelligent quick food preparation method according to claim 2, it is characterized in that, at further comprising the steps of B0 between described steps A and the step B: judge in the reasonable price interval whether the price of having a dinner that the user imports presetting, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported.
4. intelligent quick food preparation method according to claim 3 is characterized in that, described step B0 specifically comprises:
The price summation of all vegetables in B01, the computational data storehouse, the price summation of all vegetables in the database that calculates is labeled as SUM, seek cheapest vegetable in all vegetables in described database, and be MIN the price tags of described cheapest vegetable;
B02, described reasonable price interval of presetting are [MIN, SUM];
B03, judge that whether the price of having a dinner that the user imports is at [MIN, SUM] in, if, the price of having a dinner of then not adjusting the user and being imported, otherwise, adjust the price of having a dinner that the user imported, the method of the described adjustment price of having a dinner that the user imported is: if receive the information of price greater than SUM of having a dinner that the user imports, be SUM then with the price adjustment of having a dinner that the user imported, if the price of having a dinner that receives that the user imports is MIN with the price adjustment of having a dinner that the user imported then less than the information of MIN.
5. intelligent quick food preparation method according to claim 4, it is characterized in that, at further comprising the steps of B00 between described step B0 and the step B: judge obtain by step B0 have a dinner price whether in the reasonable fluctuation range of consumption valency, if, the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported.
6. intelligent quick food preparation method according to claim 5 is characterized in that, described step B00 specifically comprises:
B001, according to the number of meals that the user imported, calculate the number scope [a, b] of required pantry vegetable;
B002, according to the number scope of required pantry vegetable, calculate the ceiling price of required pantry vegetable and the floor price of required pantry vegetable, wherein, the computing method of the ceiling price of required pantry vegetable are: the price summation sum_max of b the vegetable that price is the highest in all vegetables, and the computing method of the floor price of required pantry vegetable are: the price summation sum_min of a cheapest a vegetable in all vegetables;
The reasonable fluctuation range of B003, the described consumption valency of calculating:
B003.1, according to the historical consume database of record that presets, calculate the average price and the historical pre-capita consumption volume of all vegetables;
B003.2, setting reference price are standard=Max (average price of all vegetables, historical pre-capita consumption volume), and wherein, Max is for getting max function;
The reasonable fluctuation range of B003.3, the described consumption valency of calculating is: [Max (standard* number of meals * 0.6, sum_min), Min (standard* number of meals/0.6, sum_max)], wherein, Max is for getting max function, and Min is for getting minimum value function;
B004, judge by what step B0 obtained and have a dinner price whether in the reasonable fluctuation range of described consumption valency, if the number of meals of then not adjusting the user and being imported, otherwise, adjust the number of meals that the user imported, wherein, the method for the described adjustment number of meals that the user imported is: adjusted number of meals is the ratio of have a dinner price and the described reference price obtained by step B0.
7. intelligent quick food preparation method according to claim 1, it is characterized in that, before described step C, also comprise: according to the historical consume database of record that presets, obtain the classification of each vegetable in all vegetables, and the composition of the vegetable of each classification, the random number of demarcating between the 0-100 is corresponding with each classification of vegetable;
Adopt the depth-first search algorithm in the described step e, generate in the process of vegetable combination in the vegetable from described step C after randomly ordered, utilize the method for the random number between the 0-100 that generates at random, determine the affiliated classification of vegetable of next step searching, make in seeking the result, allow the classification difference under adjacent arbitrarily two vegetables in the vegetable combination that generates as far as possible.
8. intelligent quick food preparation method according to claim 1 is characterized in that,
The computing method of the evaluation of nutrition score value summation of the nutritional labeling of the described vegetable combination in described first constraint condition are: the evaluation of nutrition score value that calculates each nutritional labeling respectively is that (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the described vegetable combination/every group to 100*Min, 1/ (branch ingestion standard amount is formed in number of meals/every per capita meal-trade of this kind nutritional labeling total amount in the combination of described vegetable/every group)), the evaluation of nutrition score value addition of each nutritional labeling that described vegetable is made up is the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination again, wherein, described every per capita meal-trade is formed branch ingestion standard amount for setting in advance;
The computing method of the fluctuation range that every group pantry price in described second constraint condition allows are:
Described every group pantry price is number of meals/described number of meals of described every group of the price * of having a dinner;
The fluctuation range that described every group pantry price allows is [every group pantry price * (1-10%), every group pantry price/(1-10%)].
9. intelligent quick food preparation method according to claim 1, it is characterized in that, adjust the method for first constraint condition among the described step G for reducing first threshold, the method of adjusting second constraint condition is for the upper limit of the fluctuation range that improves described permission or enlarge the upper and lower bound of the fluctuation range of described permission simultaneously
The method of adjusting second constraint condition among the described step H is for the upper limit of the fluctuation range that improves described permission or enlarge the upper and lower bound of the fluctuation range of described permission simultaneously.
10. an intelligent quick food preparation method is characterized in that, may further comprise the steps:
A, reception the number of meals and the price of having a dinner that the user imported;
B, described number of meals is divided into N group, obtain every group number of meals, and determine every group pantry price in described N the group, carry out pantry according to following steps respectively every group according to the price of having a dinner that the user imported, wherein, described N is the integer more than or equal to 1;
C, carry out randomly ordered to all vegetables in the database;
Be limited to T when D, setting nutrient diet, be limited to Tmax when setting the pantry program run, wherein, Tmax＞T;
E, to the vegetable after randomly ordered among the described step C, utilization depth-first search algorithm generates the combination of first vegetable;
F, judge current point in time, when described nutrient diet time limit T no show, execution in step G, when the described nutrient diet time limit, T arrived and during described pantry program run time limit Tmax no show, execution in step H, when described pantry program run time limit Tmax has arrived, execution in step I;
G, judge whether vegetable combination satisfies first constraint condition, second constraint condition and the 3rd constraint condition simultaneously, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust first constraint condition and/or second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
H, judge whether vegetable combination satisfies second constraint condition and the 3rd constraint condition, if then finish pantry, with this vegetable array output; Otherwise, further judge whether to have generated all vegetable combinations according to the depth-first search algorithm, if, then adjust second constraint condition, return step e again, otherwise, utilization depth-first search algorithm generates next vegetable combination, and returns step F;
Choose vegetable combination and output in I, the vegetable from described step C after randomly ordered in order;
Wherein, described first constraint condition is: the evaluation of nutrition score value summation of the nutritional labeling of described vegetable combination is greater than the first threshold of setting,
Described second constraint condition is: the price of described vegetable combination drops in the fluctuation range that every group pantry price allows.
Described the 3rd constraint condition is: the absolute value of the potential of hydrogen data addition summation of vegetable is less than second threshold value in the described vegetable combination, and wherein, the potential of hydrogen data of vegetable are for setting in advance in the described vegetable combination.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102651052A (en) * | 2012-03-29 | 2012-08-29 | 陶杰 | Intelligent combo type dish ordering method |
| CN104517190A (en) * | 2014-12-29 | 2015-04-15 | 东莞市新雷神仿真控制有限公司 | Diet nutrition interaction science popularization system |
| CN105989552A (en) * | 2015-02-13 | 2016-10-05 | 李翎竹 | Diet management server |
| CN109272213A (en) * | 2018-08-30 | 2019-01-25 | 成都饭轻松科技有限公司 | One kind being based on the digitized vegetable restoring method of the sense of taste |
| CN109461042A (en) * | 2018-09-13 | 2019-03-12 | 北京辰森世纪科技股份有限公司 | Intelligent nutrition food preparation method, apparatus and system |
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2009
- 2009-11-02 CN CN200910193556A patent/CN101702189A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102651052A (en) * | 2012-03-29 | 2012-08-29 | 陶杰 | Intelligent combo type dish ordering method |
| CN104517190A (en) * | 2014-12-29 | 2015-04-15 | 东莞市新雷神仿真控制有限公司 | Diet nutrition interaction science popularization system |
| CN105989552A (en) * | 2015-02-13 | 2016-10-05 | 李翎竹 | Diet management server |
| CN109272213A (en) * | 2018-08-30 | 2019-01-25 | 成都饭轻松科技有限公司 | One kind being based on the digitized vegetable restoring method of the sense of taste |
| CN109272213B (en) * | 2018-08-30 | 2022-02-01 | 成都饭轻松科技有限公司 | Dish reduction method based on taste digitization |
| CN109461042A (en) * | 2018-09-13 | 2019-03-12 | 北京辰森世纪科技股份有限公司 | Intelligent nutrition food preparation method, apparatus and system |
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