CN115809842A - Method and system for realizing intelligent air freight transportation stowage - Google Patents
Method and system for realizing intelligent air freight transportation stowage Download PDFInfo
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Abstract
The invention relates to a method and a system for realizing intelligent air freight loading, wherein the method comprises the following steps: acquiring order data during air freight transportation; constructing an objective function by taking the lowest order freight cost of the floating berth as a target; determining constraint conditions of the objective function according to the freight type and the flight date of each order; and solving the objective function to obtain the air freight mode with the lowest cost. The invention constructs the objective function by taking the lowest order freight cost of the floating cabin as the target and solves the objective function to obtain the air freight mode, thereby reducing the freight cost to the greatest extent.
Description
Technical Field
The invention relates to the technical field of air freight, in particular to an implementation method, a system, electronic equipment and a computer readable storage medium for air freight intelligent stowage.
Background
Air freight, i.e. air transport, is an important component of modern logistics and provides safe, quick, convenient and quality service. The air transportation wins a considerable market with safety, rapidness and punctuality, and greatly shortens the delivery period. However, the existing waybill allocation method only considers flight and takeoff time, so that the transportation timeliness of goods can be guaranteed, but the freight cost is greatly increased.
Disclosure of Invention
In order to solve the above problems, an object of the embodiments of the present invention is to provide a method and a system for implementing intelligent air freight transportation stowage.
An implementation method for intelligent air freight transportation stowage comprises the following steps:
step 1: acquiring order data during air freight transportation;
step 2: constructing an objective function by taking the lowest order freight cost of the floating berth as a target;
and step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
and 4, step 4: and solving the objective function to obtain the air freight mode with the lowest cost.
Preferably, the objective function in step 2 is:
wherein N is the order quantity of one main multiple-divided type, M is the order quantity of straight order or one main divided type, F (MAWBCW) i ,RCCP j ) Cost of orders on or in one main minute, F (MAWBCW) k ,RCCP j ) The cost of an order that is a master multiple.
Preferably, the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, wherein the constraint conditions comprise:
when an order of a direct order or a main-minute type goes into a package cabin, the constraint conditions of the objective function are as follows:
wherein, the order set of the direct order or one main and one minute is OA i The set of bunkers is FC { FC 1 ，FC 2 ，…,FC L }，X ik =0 or 1 (1 means straight order or one main order i. Go to package bin FC k 0 represents a direct single or a mainOne-minute order i non-walk package cabin FC k ) And i =1,2, \8230;, M, k =1,2, \8230;, L, OA (OP) i ) FC (FCOP) as the origin of the order or a primary order entry i k ) For containing FC k OA (DP) i ) FC (FCDP) as destination port for a direct order or a primary order-dividing order i k ) For containing FC k Oako Gao, OA (EETD) i ) Earliest takeoff time, FC (FCETD), for a direct order or a primary order entry i k ) For containing FC k Time of departure, OA (LETD) i ) Latest takeoff time, OA (GW) for a standing order or a main order I i ) Gross weight, OB (GW) of order j being a master order or one master one minute i ) Gross weight of order i, FCMAXGW, for one master with multiple scores k For containing FC k Maximum gross weight of (3), OA (VW) i ) The volume weight of order j, OB (VW), being a main order or a main minute i ) Volume weight of order i, FCMAXVW, being one master with multiple points k For containing FC k Is the maximum volume weight of.
Preferably, the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, and further comprising:
when the order of the direct order or the main-minute type does not go through the package, the constraint conditions of the objective function are as follows:
wherein the set of non-containing chambers is UFC { UFC 1 ，UFC 2 ，…,UFC W }，Y ik =0 or 1 (1 means current order i walk non-bag UFC k And 0 represents that the current order i cannot walk on the UFC without covering the cabin k )，k＝1,2,…,W，UFC(UFCOP k ) For UFC without covering cabin k UFC (UFCDP) k ) For UFC without covering cabin k UFC (UFCETD) of the Port of origin k ) For UFC without covering cabin k Takeoff time of UFCMAXGW k For UFC without covering cabin k UFCMAXVW k For UFC without covering cabin k Is the maximum volume weight of.
Preferably, the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, and further comprising the following steps:
when the order of one main multi-branch type does not go into the packing compartment, and the current order is assembled with other orders, namely when Y ik ＝1，Z ij When =1, the constraint condition of the objective function is:
in the formula, Y ik =1 order of multi-division type i-go non-package UFC k ，Z ij =1 orders i and j are put together, OB (OP) i ) OB (OP) being the origin of an order i of the one-master multiple-minute type j ) OB (DP) being the Port of origin of an order j of the one-master multispindle type i ) OB (DP) being the destination Port of an order i of the one-master-multiscale type j ) OB (EETD) as the destination Port of an order j of a primary multiple-minute type i ) Earliest takeoff time, OB (LETD), of order i of one-master multiple-minute type i ) Latest departure time, OB (EETD) for an order i of the one-master multiple-minute type j ) Earliest takeoff time, OB (LETD), of order j of one-master multiple-minute type j Latest takeoff time of order j of one-master multi-minute type, MAWBCW i Is, GW j Gross weight, VW, of order j of one-master-multiple-minute type j The volume of order j, which is a master multi-score type.
Preferably, when a primary multi-category order does not go into a parcel compartment and the current order is pieced together with other orders, the objective function charges a primary multi-category order in a manner that:
wherein, Y ik =1 (1 denotes the current order of one main multi-point, i walk off package k), i =1,2, \ 8230;, N, k =1,2, \ 8230;, W, number of non-packages, Z ij =0 or 1 (1 means order i and j are put together)0 indicates that orders i and j are not spliced together), i =1,2, \ 8230;, N, j =1,2, \ 8230;, N, FRCCP j For the charging re-freight rate function, ceil is the charging re-lean level adjustment function, RC j The rating override function is charged.
The invention also provides a method for realizing the intelligent air freight transportation stowage, which comprises the following steps:
the order data acquisition module is used for acquiring order data during air freight transportation;
the objective function constructing module is used for constructing an objective function by taking the lowest order freight cost of the floating berth as a target;
the constraint condition determining module is used for determining the constraint conditions of the objective function according to the freight type and the flight date of each order;
and the objective function solving module is used for solving the objective function to obtain the air freight mode with the lowest cost.
The invention also provides an electronic device, which comprises a bus, a transceiver, a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the transceiver, the memory and the processor are connected through the bus, and the computer program realizes the steps in the implementation method of the air freight transportation intelligent stowage when being executed by the processor.
The invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the implementation method of the air freight intelligent stowage.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention relates to an implementation method, a system, electronic equipment and a computer readable storage medium for intelligent air freight transportation stowage, wherein the method comprises the following steps: acquiring order data during air freight transportation; constructing an objective function by taking the lowest order freight cost of the floating berth as a target; determining constraint conditions of the objective function according to the freight type and the flight date of each order; and solving the objective function to obtain the air freight mode with the lowest cost. The invention constructs the objective function by taking the lowest order freight cost of the floating cabin as the target and solves the objective function to obtain the air freight mode, thereby reducing the freight cost to the greatest extent.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an implementation method for air freight transportation intelligent stowage provided by the invention.
Detailed Description
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are used merely for convenience of description and simplification of the description, but do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, an implementation method of air freight intelligent stowage includes:
step 1: acquiring order data during air freight transportation;
in practical applications, the order data in the present invention can be defined as:
1. set of current orders is O = { O = { (O) 1 ，O 2 ，…,O K }，O i (i =1, \8230;, K) is defined as an array { origin port, destination port, gross weight, bulk weight, earliest takeoff time, latest takeoff time }, herein denoted by { OP } i ，DP i ，GW i ，VW i ，EETD i ,LETD i Denotes. MaxLETD = Max (O (LETD)), the largest latest departure time in the order set.
2. The current order set, in which the customer requirements must be a straight order or a one-main-one-minute order, is: OA = { OA = 1 ，OA 2 ，…OA M }. A master list: the freight bill handed to the navigation department during air freight transportation can be divided into a plurality of sub-bills under one main bill; straightening: a main order without a separate order is arranged under one main order;
3. the remaining order set of one prime score is OB = { OB = 1 ，OB 2 ，…OB N }。M+N＝K
4. The set of the packet compartments from the current time to the MaxLETD is FC = { FC = { (FC) 1 ，FC 2 ，…,FC L },FC i (i =1, \8230;, L) is defined as an array { origin port, destination port, maximum gross weight, maximum bulk weight, departure time, freight }, here by { FCOP } i ，FCDP i ，FCMAXGW i ，FCMAXVW i ，FCETD i ,CF i Represents it.
5. UFC (= { UFC) = UFC for flight set with non-package in MaxLETD from current time 1 ，UFC 2 ，…,UFC L },UFC i (i =1, \ 8230;, W) is defined as an array { origin Port, destination Port, maximum gross weight } maximumVolume weight, takeoff time, M freight rate, N freight rate, 45 freight rate, 100 freight rate, 300 freight rate, 500 freight rate, 1000 freight rate, used herein as { FCOP } i ，FCDP i ，FCMAXGW i ，FCMAXVW i ，FCETD i ,M i ,N i ,45 i ,100 i ,300 i ,500 i ,1000 i Denotes.
Step 2: and constructing an objective function by taking the lowest order freight cost of the floating berth as a target.
Further, the objective function in the present invention is:
where N is the order quantity of a one-major-multiple-minute type, M is the order quantity of a direct order or a one-major-one-minute type, and F (MAWBCW) i ,RCCP j ) Cost of an order that must be either primary or one-primary-one-minute for the customer demand in the current order, F (MAWBCW) k ,RCCP j ) The cost of the remaining one-master-multiple order.
It should be noted that the cost of the main unit freight for the floating bay is the lowest (actually, the sum of the main unit freight for the floating bay + the main unit freight for the fixed bay is the lowest, but since the fixed bay is fixed, the present invention only calculates the floating bay).
And 3, step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
further, step 3 comprises:
when an order of a direct order or a main-minute type goes into a package cabin, the constraint conditions of the objective function are as follows:
wherein, the order set of the order list or one main and one minute is OA i The set of bunkers is FC { FC 1 ，FC 2 ，…,FC L }，X ik ＝0Or 1 (1 denotes the current order i to go to the packing bin FC k And 0 represents that the current order i does not go to the packing bin FC k ) And i =1,2, \ 8230;, M, k =1,2, \ 8230;, L, OA (OP) i ) FC (FCOP) for the Port of origin of the current order i k ) For containing FC k OA (DP) i ) FC (FCDP) for the Port of origin and destination of the Current order i k ) For containing FC k OA (EETD) i ) For the earliest takeoff time of the current order i, FC (FCETD) k ) For containing FC k Takeoff time of (OA), (LETD) i ) OA (GW) time of latest takeoff for current order i i ) Gross weight, OB (GW) of order j being a primary order or a primary score i ) Gross weight of order i, FCMAXGW, for one-master multiple minute k For containing FC k Maximum gross weight of (OA) (VW) i ) The volume weight of order j, OB (VW), being a main order or a main minute i ) Volume weight of order i, FCMAXVW, for one-master multiple k For containing FC k Is the maximum volume weight of.
When the order of the direct order or the main-minute type does not go through the package, the constraint conditions of the objective function are as follows:
wherein the set of non-containing chambers is UFC { UFC 1 ，UFC 2 ，…,UFCW}，Y ik =0 or 1 (1 represents current order i walk non-package UFC k And 0 represents that the current order i cannot walk on the UFC without covering the cabin k )，k＝1,2,…,W，UFC(UFCOP k ) For UFC without covering cabin k UFC (UFCDP) k ) For UFC without covering cabin k UFC (UFCETD) of the Port of origin and destination k ) For UFC without covering cabin k Takeoff time of UFCMAXGW k For UFC without covering cabin k UFCMAXVW k For UFC without covering cabin k Is heavy in maximum volume.
When an order of a main multi-branch type does not go through a parcel and the current order is assembled with other orders, the constraint conditions of the objective function are as follows:
when the order of one main multi-branch type does not go into the packing compartment, and the current order is assembled with other orders, namely when Y ik ＝1，Z ij =1, the constraint condition of the objective function is:
in the formula, Y ik =1 order i-walk non-package UFC with one main multi-branch type k ，Z ij =1 orders i and j are put together, OB (OP) i ) OB (OP) being the origin of an order i of the one-master multiple-minute type j ) OB (DP) as the origin of an order j of the one-master multi-minute type i ) OB (DP) being the destination Port of an order i of one-master multiple-minute type j ) OB (EETD) being the destination of an order j of the one-master-multiscale type i ) Earliest takeoff time, OB (LETD), of order i of one-master multiple-minute type i ) Latest departure time, OB (EETD) for an order i of the one-master multiple-minute type j ) Earliest takeoff time, OB (LETD), of order j of one-master multiple-minute type j MAWBCW as the latest takeoff time of an order j of the one-master multiple-minute type i Is, GW j Gross weight, VW, of order j of one-master-multiple-minute type j The volume of order j, which is a master multi-score type.
The construction process of the constraint condition of the present invention is further explained by combining with the specific embodiment as follows:
1. and judging whether the current order is taken into a packing box or not and which flight date is taken into the packing box.
Order set OA for primary order or primary-to-secondary i And the set of pods is FC { FC 1 ，FC 2 ，…,FC L }. Covering a cabin: the air freight forwarder must be in charge of the driver to fix the amount of freight of a specific weight on each flight of the flight.
X ik =0 or 1 (1 denotes the current order i takes a parcel bay k), i =1,2, \ 8230;, M, k =1,2, \ 8230
101. One order can only be put into one compartment and is not divided into 2 compartments.
Order set OB for one master multiple i Similarly as above.
102. The starting port and the destination port of the order are equal to the starting port and the destination port of the package;
order set OA for primary order or one primary one secondary i ，
OA(OP i )＝FC(FCOP k ) If X is ik ＝1
OA(DP i )＝FC(FCDP k ) If X is ik ＝1
Order set OB for one master multiple i Similarly as above.
103. The earliest takeoff time and the latest takeoff time of the order comprise the takeoff time of the package cabin flight;
OA(EETD i )<＝FC(FCETD k ) If X is ik ＝1
OA(LETD i )>＝FC(FCETD k ) If X is ik ＝1
Order set OB for one master multiple i Similarly as above.
104. The sum of the volume weight of the orders of the luggage compartment is lower than the maximum gross weight of the luggage compartment;
105. the gross weight sum of the orders of the luggage compartment is lower than the maximum volume weight of the luggage compartment
For the order with one main order and one straight order and one main order and more orders, the packing compartment is taken, and the grading and bubble eating of the main order are not required to be considered due to the fixed transportation cost of the packing compartment;
2. judging whether the current order does not go into the package cabin or which flight date to go when the current order goes to the flight
Order set OA for primary order or primary-to-secondary i And the set of non-containing chambers is UFC { UFC 1 ，UFC 2 ，…,UFC W }。
Y ik =0 or 1 (1 means current order i walk away non-contracting bay k), i =1,2, \8230;, M, k =1,2, \8230;, W
201. One order can only be used for a flight without a package or a package, and the flight cannot simultaneously go through the package and the non-package.
202. One order can only be used for one flight without a cabin, and the order is not divided into 2 flights.
Order set OB for one master multiple i Similarly as above.
203. The starting port and the destination port of the order are equal to the starting port and the destination port of the parcel;
order set OA for primary order or one primary one secondary i ，
OA(OP i )＝UFC(UFCOP k ) If Y is ik ＝1
OA(DP i )＝UFC(UFCDP k ) If Y is ik ＝1
Order set OB for one master multiple i Similarly as above.
204. The earliest take-off time and the latest take-off time of the order comprise the take-off time of the cabin flight;
OA(EETD i )<＝UFC(UFCETD k ) If Y is ik ＝1
OA(LETD i )>＝UFC(UFCETD k ) If Y is ik ＝1
Order set OB for one master multiple i Similarly as above.
205. The sum of the volume weights of the orders for taking the non-covered cabin is lower than the maximum gross weight of the non-covered cabin;
206. the gross weight sum of the orders for walking the non-covered cabin is lower than the maximum volume weight of the non-covered cabin
For a primary score and straight order set OA, the order of the primary orders is considered. A master multi-point order set OB needs to consider the level of the master order and the amalgamation bubbles. Grading: the air freight rates are classified into freight rates of different weight grades of M, N,45,100,300,500, and if the freight rate of a certain weight grade multiplied by the lowest weight of the weight grade is lower than the product of the actual weight multiplied by the freight rate of the corresponding grade, the carrier can make a bill and declare the weight according to the lowest weight of the weight grade. For example, a 100 kg shipping rate of 1,300 kg is 0.9, and if 299 kg of freight is greater than 300 x 0.9, the carrier may grade the weight of the freight to 300 (rather than 299) and move the freight rate to 300 kg, thus resulting in a lower overall shipping cost. Gathering and eating bubbles: the air cargo is multiplied by 1000 according to the volume (cubic meter) and divided by 6 to obtain the volume weight (kilogram), if the volume weight is higher than the gross weight, the volume weight is taken as the charging weight of the pickled goods, otherwise, the gross weight is taken as the charging weight, and the charging of the main bill is reduced to be lower than the sum of the gross weights of all the branch bills and also lower than the sum of the volume weights of all the branch bills by matching the pickled goods and the heavy goods.
2.1 the current order OB with one main multi-point does not go through the packing compartment, and the current order is assembled with other orders.
If Y is ik =1 (1 denotes the current master-slave systemThe divided order i leaves no bay k), i =1,2, \ 8230;, N, k =1,2, \ 8230;, W,
Z ij =0 or 1 (1 means that orders i and j are pieced together), i =1,2, \8230;, N, j =1,2, \8230;, N,
2.1.1 the origin port and the destination port of the assembled order are equal;
OB(OP i )＝OB(OP j ) If Y is ij ＝1
OB(DP i )＝OB(DP j ) If Y is ij ＝1
2.1.2 the earliest take-off time and the latest take-off time of the gathering order form have intersection;
{OB(EETD i ),OB(LETD i )}∩{OB(EETD j )，OB(LETD j ) }! = Null if Y ij ＝1
2.2 weight dependent ranking of Main sheet
For a primary multi-point order set OB, if Y ik =1 (1 indicates that the current order of a main multi-division, i, leaves a non-parcel k), i =1,2, \ 8230; N, k =1,2, \ 8230; W,
Z ij =0 or 1 (1 indicates that orders i and j are pieced together), i =1,2, \8230;, N, j =1,2, \8230;, N, the current non-enclosed order OB i Corresponding charging is repeated
The first branch shows that if the order and other orders are pieced together into a main order, the gross weight sum and the volume weight sum of the orders are compared, and the large value is taken as the charging weight of the main order
The business implication of the second branch is that if the current order has been pieced together with the previous order into a main order, the main order is charged without repeated calculations.
And defining a function F as a function of the freight charge of the current master bill after the charging weight of the master bill and the freight rate of the flight are given.
F(MAWBCW i ，RCCP j )＝min{MAWBCW i *FRCCP j (MAWBCW i )，
min(ceil(RC j (MAWBCW i ))，FRCCP j (ceil(RC j (MAWBCWi)))}
i＝1，2，...，N，j＝1，2，...，W
And defining a charging re-leaning level function RC to give the charging weight, and returning a maximum kilogram level lower than the current charging weight.
The set of RC return values = { M, N,45,100,300,500, 1000}.
For example, RC (88) =45, RC (101) =100
The current freight rate is RCCP k ＝RCPC(M) k ，RCPC(N) k ，RCPC(45) k ，RCPC(100) k ，RCPC(300) k ，RCPC(500) k ，RCPC(1000) k 。k＝1，2，...，W
And defining a charging freight rate function FRCCP as a given charging freight, returning the freight rate suitable for the current charging freight, and taking the set returned by the function as RCCP.
And defining the charging emphasis level adjustment function ceil as the lowest kilogram level which is larger than the current charging weight.
If MAWBCW i *RC(MAWBCW i )＞ceil(MAWBCW i )*RC(ceil(MAWBCW i ) Then MAWBCW) i ＝ceil(MAWBCW i )。
For example, 299 corresponds to a freight rate of 100 in kilograms (1 yuan per kilogram), greater than 299 and a lowest in kilograms of 300, 300 in kilograms, 0.9 yuan per kilogram.
The principle is the same for a primary-one-minute and straight-single set OA.
And 4, step 4: and solving the objective function to obtain the air freight mode with the lowest cost.
Since the optimization process cannot be evaluated by methods such as a simplex method, a simulated annealing algorithm is required to solve the problem. The solving process is as follows:
setting initial temperature t = t max ,
The solution for each order is defined by three values: the flight date of which the flight is taken, the non-flight number (these 2 are mutually exclusive), and those orders are configured as a master order.
The origin and destination of the initial solution to the order are defined to be equal to the origin and destination of the parcel, and the flight date and time is the earliest flight in the flight. Up until the total volume or weight of orders for booking a cabin-to-package flight exceeds 80% of the maximum volume or weight (empirical value). And then take the next earliest flight in the flight. The loop continues until all flight packages exceed 80% of the maximum volume or weight (empirical values).
The remaining orders then take orders with origin and destination ports equal to those of the non-enclosed flight with the earliest flight date and time. Up until the total volume or weight of orders for non-inclusive flights exceeds 80% of the maximum volume or weight (empirical value). Then the non-flight with the second earliest date and time is taken and the process is continued.
If the flight date is one master, the date of the same flight is one master.
Before initialization, the orders are arranged in a group of the origin port + the destination port + the latest departure time of flights, then the orders are sorted from large to small according to the charging weight of the orders (the orders with heavy weight are preferentially ordered, and the earlier flights are ordered), and then initialization is carried out. The set of initial solutions r is initialized by the above process.
Internal circulation
Randomly selecting a solution r from r neighborhood t Calculating r and r t Corresponding to the value of the objective function E, e.g. r t If the corresponding objective function value is smaller, let r = r t (ii) a Otherwise if
Let r = r t .
Here the neighborhood of r is constructed in 2 sets of random ith significant values (the following sets may have N significant values, the system generates a random number Y of 1 to N by N, and then takes the ith significant value by the random number Y):
the starting port and the destination port of the order are equal to the starting port and the destination port of the packing cabin, the remaining cabin spaces on the packing cabin can contain the weight and the volume of the order, and the flight date is smaller than the earliest takeoff time of the order and is larger than the latest takeoff time of the order.
The starting port and the destination port of the order are equal to the starting port and the destination port of the non-packing chamber, the non-packing chamber has the rest space for packing the weight and the volume of the order, and the flight date is less than the earliest takeoff time of the order and is more than the latest takeoff time of the order.
If the internal circulation stop condition is not satisfied (1, the mean value of the target function E is stable 2, the target values of a plurality of continuous steps are changed less 3, and the fixed sampling step number), repeating the previous step of external circulation
Temperature reduction t = dew (t)
If the external circulation stopping condition is not met, the second step is carried out (1, the termination temperature is reached, 2, the iteration times are reached, 3, the optimal value is continuously kept unchanged for a plurality of steps); otherwise the algorithm ends.
The method constructs the objective function by taking the lowest order freight cost of the floating bay as a target, and solves the objective function by utilizing a simulated annealing algorithm to obtain an air freight transportation mode, so that the freight transportation cost can be reduced to the greatest extent.
The invention also provides a method for realizing the intelligent air freight transportation stowage, which comprises the following steps:
the order data acquisition module is used for acquiring order data during air freight transportation;
the objective function constructing module is used for constructing an objective function by taking the lowest order freight cost of the floating berth as a target;
the constraint condition determining module is used for determining the constraint conditions of the objective function according to the freight type and the flight date of each order;
and the objective function solving module is used for solving the objective function to obtain the air freight mode with the lowest cost.
Compared with the prior art, the beneficial effects of the implementation system for the intelligent air freight transportation stowage provided by the invention are the same as the beneficial effects of the implementation method for the intelligent air freight transportation stowage provided by the technical scheme, and the detailed description is omitted here.
The embodiment of the present invention further provides an electronic device, which includes a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the transceiver, the memory, and the processor are connected via the bus, respectively, and when the computer program is executed by the processor, the processes in the embodiment of the implementation method for intelligent air freight transportation loading are implemented, and the same technical effects can be achieved, and are not described herein again to avoid repetition.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements each process of the embodiment of the implementation method for intelligent air freight transportation, and can achieve the same technical effect, and in order to avoid repetition, the computer program is not described herein again.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present invention, and the present invention shall be covered by the claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. An implementation method for intelligent air freight transportation stowage is characterized by comprising the following steps:
step 1: acquiring order data during air freight transportation;
step 2: constructing an objective function by taking the lowest order freight cost of the floating berth as a target;
and 3, step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
and 4, step 4: and solving the objective function to obtain the air freight mode with the lowest cost.
2. The method for implementing intelligent air cargo transportation loading according to claim 1, wherein the objective function in the step 2 is as follows:
wherein N is the order quantity of a primary multi-point type, M is the order quantity of a direct order or a primary multi-point type, FMAWBCW i ,RCCP j Cost of orders for primary order or one primary minute, FMAWBCW k ,RCCP j The cost of an order that is a primary multiple.
3. The method for realizing the intelligent air cargo loading according to claim 2, wherein the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, wherein the constraint conditions comprise:
when an order of a direct order or a main-minute type goes into a package cabin, the constraint conditions of the objective function are as follows:
wherein, the order set of the direct order or one main and one minute is OA i The set of bunkers is FC { FC 1 ，FC 2 ，…,FC L }，X ik =0 or 1 (1 means straight order or one main order i. Go to package bin FC k 0 indicates that the order is straight or a main order I does not go into the packing box FC k ) And i =1,2, \ 8230;, M, k =1,2, \ 8230;, L, OA (OP) i ) FC (FCOP) as the origin of a direct order or a primary order i k ) For containing FC k OA (DP) i ) FC (FCDP) as destination port for a direct order or a primary order-dividing order i k ) For containing FC k OA (EETD) i ) Earliest takeoff time, FC (FCETD), for a direct order or a primary order entry i k ) For containing FC k Time of departure, OA (LETD) i ) Latest takeoff time, OA (GW) for a standing order or a main order I i ) Orders as principal orders or one principal and one minuteGross weight of j, OB (GW) i ) Gross weight of order i, FCMAXGW, for one master with multiple scores k For containing FC k Maximum gross weight of (OA) (VW) i ) The volume weight of order j, OB (VW), being a main order or a main minute i ) Volume weight of order i, FCMAXVW, for one-master multiple k For containing FC k Is the maximum volume weight of.
4. The method for realizing the intelligent air freight transportation stowage according to claim 3, wherein the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, and further comprising the following steps:
when the order of the direct order or the main-minute type does not go through the package, the constraint conditions of the objective function are as follows:
wherein the set of non-containing chambers is UFC { UFC 1 ，UFC 2 ，…,UFC W }，Y ik =0 or 1 (1 represents current order i walk non-package UFC k And 0 represents that the current order i cannot walk on the UFC without covering the cabin k )，k＝1,2,…,W，UFC(UFCOP k ) For UFC without covering cabin k UFC (UFCDP) k ) For UFC without covering cabin k UFC (UFCETD) of the Port of origin and destination k ) For UFC without covering cabin k Takeoff time of UFCMAXGW k For UFC without covering cabin k UFCMAXVW k For UFC without covering cabin k Is heavy in maximum volume.
5. The method for realizing the intelligent air cargo loading according to claim 4, wherein the step 3: determining the constraint conditions of the objective function according to the freight type and the flight date of each order, and further comprising:
when the order of one main multi-classification type does not go into the compartment, and the current order is assembled with other orders, namely when Y ik ＝1，Z ij When =1, theThe constraints of the objective function are:
in the formula, Y ik =1 order i-walk non-package UFC with one main multi-branch type k ，Z ij =1 orders i and j are put together, OB (OP) i ) OB (OP) being the origin of an order i of the one-master multiple-minute type j ) OB (DP) being the Port of origin of an order j of the one-master multispindle type i ) OB (DP) being the destination Port of an order i of the one-master-multiscale type j ) OB (EETD) as the destination Port of an order j of a primary multiple-minute type i ) Earliest takeoff time, OB (LETD), of order i of one-master multiple-minute type i ) Latest departure time, OB (EETD) for order i of one-master multiple-minute type j ) Earliest departure time, OB (LETD) of an order j of the type one-master multiple j Latest takeoff time of order j of one-master multi-minute type, MAWBCW i Is, GW j Gross weight, VW, of order j of one-master-multiple-minute type j The volume of order j, which is a master multi-score type, is heavy.
6. The method according to claim 5, wherein when the primary multi-category order does not go into the parcel compartment and the current order is pieced together with other orders, the objective function charges the primary multi-category order in a manner that:
wherein, Y ik =1 (1 represents that the current order of one main multi-division i walks through non-package k), i =1,2, \ 8230, N, k =1,2, \ 8230, W is the number of non-package, Z ij =0 or 1 (1 means order i and j are pieced together, 0 means order i and j are not pieced together), i =1,2, \8230;, N, j =1,2, \8230;, N, FRCCP j For the billing Re-freight Rate function, ceil for the billing Re-lean level adjustment function, RC j The rating override function is charged.
7. An implementation method for intelligent air freight transportation stowage is characterized by comprising the following steps:
the order data acquisition module is used for acquiring order data during air freight transportation;
the objective function constructing module is used for constructing an objective function by taking the lowest order freight cost of the floating berth as a target;
the constraint condition determining module is used for determining the constraint conditions of the objective function according to the freight type and the flight date of each order;
and the objective function solving module is used for solving the objective function to obtain the air freight mode with the lowest cost.
8. An electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory and the processor are connected via the bus, and wherein the computer program, when executed by the processor, implements the steps of a method for implementing an air freight intelligent stowage according to any one of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of a method for carrying out an intelligent air-freight stowage according to any one of claims 1 to 6.
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