CN115809842B - Implementation method and system for intelligent allocation of air freight - Google Patents
Implementation method and system for intelligent allocation of air freight Download PDFInfo
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Abstract
The invention relates to a method and a system for realizing intelligent allocation of air freight, wherein the method comprises the following steps: acquiring order data in the air freight transportation process; constructing an objective function by taking the lowest order freight cost of the floating bunk 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. According to the invention, the objective function is constructed by taking the lowest order freight cost of the floating bunk as the objective, and the objective function is solved to obtain the air freight mode, so that the freight cost can be reduced to the greatest extent.
Description
Technical Field
The invention relates to the technical field of air freight, in particular to a method, a system, electronic equipment and a computer readable storage medium for realizing intelligent allocation of air freight.
Background
Air freight, i.e. air freight, is an important component of modern logistics and provides safe, fast, convenient and quality service. The air traffic wins a quite large market on time safely and rapidly, and the delivery period is greatly shortened. However, the existing bill loading mode only considers the flight and take-off time, so that the freight cost is greatly increased although the freight timeliness of the freight can be ensured.
Disclosure of Invention
In order to solve the above problems, an embodiment of the present invention is to provide a method and a system for implementing intelligent allocation of air freight.
An implementation method for intelligent allocation of air freight, comprising the following steps:
Step 1: acquiring order data in the air freight transportation process;
step 2: constructing an objective function by taking the lowest order freight cost of the floating bunk as a target;
Step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
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:
Where N is the number of orders of a main multi-split type, M is the number of orders of a main one-split type, F (MAWBCW i,RCCPj) is the cost of the main order or of the main one-split order, and F (MAWBCW k,RCCPj) is the cost of the main multi-split order.
Preferably, the step 3: determining constraints of the objective function according to the freight type and the flight date of each order, including:
when the order is a straight order or a main one-branch type order is a parcel cabin, the constraint condition of the objective function is as follows:
wherein the set of orders for a straight order or a main part is OA i, the set of bags is FC { FC 1,FC2,…,FCL},Xik = 0 or 1 (1 means that the straight order or a main part order i is taken by the bags FC k, 0 means that the straight order or a main part order i is not taken by the bags FC k), and i = 1,2, …, M, k = 1,2, …, L, OA (OP i) is the origin of the straight order or a main part order i, FC (FCOP k) is the origin of the bags FC k, OA (DP i) is the destination of the straight order or a main part order i, FC (FCDP k) is the destination of the bags FC k, OA (EETD i) is the earliest take-off time of the straight order or a main part order i, FC (FCETD k) is the take-off time of the bags FC k, OA (le i) is the latest take-off time of the straight order or a main part order i, OA (i) is the main part order i, OA (OB) is the main part order i, and is the most important main part of the bags (vw48) and is the volume of the most important bags (i) and (vw48) is the main part of the bags (32) and the main part of the main part (i) is the main part of the order i).
Preferably, the step 3: determining constraints of the objective function according to the freight type and the flight date of each order, and further comprising:
when the order of the straight order or the main one-branch type does not go through the package cabin, the constraint condition of the objective function is as follows:
Wherein the collection of non-capsule is UFC { UFC 1,UFC2,…,UFCW},Yik =0 or 1 (1 indicates that current order i walks non-capsule UFC k, 0 indicates that current order i does not walk non-capsule UFC k),k＝1,2,…,W,UFC(UFCOPk) is the originating port of non-capsule UFC k, UFC (UFCDP k) is the originating port of non-capsule UFC k, UFC (UFCETD k) is the takeoff time of non-capsule UFC k, UFCMAXGW k is the maximum gross weight of non-capsule UFC k, UFCMAXVW k is the maximum bulk weight of non-capsule UFC k.
Preferably, the step 3: determining constraints of the objective function according to the freight type and the flight date of each order, and further comprising:
When a main multi-branch type order does not go through the package cabin and the current order is assembled with other orders, namely when Y ik＝1,Zij =1, the constraint condition of the objective function is as follows:
Where Y ik = 1 indicates that an order of primary multi-type i leaves non-package UFC k,Zij = 1 indicates that orders i and j are pieced together, OB (OP i) is the originating port of an order of primary multi-type i, OB (OP j) is the originating port of an order of primary multi-type j, OB (DP i) is the destination port of an order of primary multi-type i, OB (DP j) is the destination port of an order of primary multi-type j, OB (EETD i) is the earliest take-off time of an order of primary multi-type i, OB (LETD i) is the latest take-off time of an order of primary multi-type i, OB (LETD j) is the latest take-off time of an order of primary multi-type j, MAWBCW i is GW j is the gross weight of an order of primary multi-type j, and VW j is the volumetric weight of an order of primary multi-type j.
Preferably, when a main multi-classification order does not go through the package cabin and the current order is assembled with other orders, the charging mode of the objective function for the main multi-classification order is as follows:
Wherein Y ik =1 (1 indicates that the order i of the current main multi-branch goes to non-package k), i=1, 2, …, N, k=1, 2, …, W, is the number of non-package, Z ij =0 or1 (1 indicates that the orders i and j are pieced together, 0 indicates that the orders i and j are not pieced together), i=1, 2, …, N, j=1, 2, …, N, FRCCP j is a billing re-freight rate function, ceil is a billing re-stage adjustment function, and RC j is a billing re-stage function.
The invention also provides an implementation method of intelligent air freight stowage, which comprises the following steps:
The order data acquisition module is used for acquiring order data in the air freight transportation process;
the objective function construction module is used for constructing an objective function by taking the lowest cost of the order freight of the floating bunk as the objective;
The constraint condition determining module is used for determining the constraint condition 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 in 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 method for realizing the intelligent allocation of air freight when being executed by the processor.
The invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps in the method for implementing the intelligent allocation of air freight.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
The invention relates to a realization method, a system, electronic equipment and a computer readable storage medium for intelligent allocation of air freight, wherein the method comprises the following steps: acquiring order data in the air freight transportation process; constructing an objective function by taking the lowest order freight cost of the floating bunk 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. According to the invention, the objective function is constructed by taking the lowest order freight cost of the floating bunk as the objective, and the objective function is solved to obtain the air freight mode, so that the freight cost can be reduced to the greatest extent.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of an implementation method for intelligent allocation of air freight.
Detailed Description
In the description of the present invention, it should 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", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," "secured," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1, a method for implementing intelligent allocation of air freight includes:
Step 1: acquiring order data in the air freight transportation process;
In practical applications, the order data in the present invention can be defined as:
1. The set of current orders is o= { O 1,O2,…,OK},Oi (i=1, …, K) defined as an array { origin port, destination port, gross weight, bulk weight, earliest take-off time, latest take-off time }, denoted here by { OP i,DPi,GWi,VWi,EETDi,LETDi }. MaxLETD = Max (O (LETD)), i.e. the maximum latest take-off time in the set of orders.
2. The customer requirements in the current order must be either straight or a prime split of the order set: oa= { OA 1,OA2,…OAM }. Main sheet: the freight list submitted to the airline company during air freight can be provided with a plurality of orders under one main list; straight sheet: a main bill without a sub bill under the main bill;
3. The remaining set of orders for one main multiple is ob= { OB 1,OB2,…OBN }. M+n=k
4. The aggregate of the pods from the current time to MaxLETD is fc= { FC 1,FC2,…,FCL},FCi (i=1, …, L) defined as an array { origin port, destination port, maximum gross weight, maximum bulk weight, take-off time, freight }, here denoted by { FCOP i,FCDPi,FCMAXGWi,FCMAXVWi,FCETDi,CFi }.
5. The flight set with non-cabins from the current time to MaxLETD is ufc= { UFC 1,UFC2,…,UFCL},UFCi (i=1, …, W) defined as an array { originating port, destination port, maximum gross weight, maximum bulk weight, departure time, M freight rate, N freight rate, 45 freight rate, 100 freight rate, 300 freight rate, 500 freight rate, 1000 freight rate }, here denoted {FCOPi,FCDPi,FCMAXGWi,FCMAXVWi,FCETDi,Mi,Ni,45i,100i,300i,500i,1000i}.
Step 2: and constructing an objective function by taking the lowest cost of the order freight of the floating bunk as a target.
Further, the objective function in the present invention is:
Where N is the number of orders of a master multi-branch type, M is the number of orders of a master one-branch type, F (MAWBCW i,RCCPj) is the cost of the order in the current order that the customer requirement must be either a master order or a master one-branch, and F (MAWBCW k,RCCPj) is the cost of the remaining one-master multi-branch orders.
It should be noted that, the cost of the main single freight of the floating bunk is the lowest (actually, the sum of the main single freight of the floating bunk and the main single freight of the fixed bunk is the lowest, but since the cost of the fixed bunk is fixed, the invention only calculates the floating bunk).
Step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
further, step3 includes:
when the order is a straight order or a main one-branch type order is a parcel cabin, the constraint condition of the objective function is as follows:
Wherein the set of orders for a straight order or a prime fraction is OA i, the set of packages is FC { FC 1,FC2,…,FCL},Xik = 0 or 1 (1 means that current order i walks package FC k, 0 means that current order i does not walk package FC k), and i = 1,2, …, M, k = 1,2, …, L, OA (OP i) is the origin port of current order i, FC (FCOP k) is the origin port of package FC k, OA (DP i) is the destination port of current order i, FC (FCDP k) is the destination port of package FC k, OA (EETD i) is the earliest take-off time of current order i, FC (FCETD k) is the take-off time of package FC k, OA (LETD i) is the latest take-off time of current order i, OA (i) is the gross weight of a prime order or a prime fraction of order j, GW (i) is the gross weight of a multiple prime order i, FC (FCDP k) is the largest volume of order i, and one prime order FC (fj) is the largest volume of multiple order 7248, and one prime order c (fj) is the largest volume of multiple of one prime order 7257.
When the order of the straight order or the main one-branch type does not go through the package cabin, the constraint condition of the objective function is as follows:
Wherein the collection of non-capsule is UFC { UFC 1,UFC2,…,UFCW},Yik =0 or 1 (1 indicates that current order i walks non-capsule UFC k, 0 indicates that current order i does not walk non-capsule UFC k),k＝1,2,…,W,UFC(UFCOPk) is the originating port of non-capsule UFC k, UFC (UFCDP k) is the originating port of non-capsule UFC k, UFC (UFCETD k) is the takeoff time of non-capsule UFC k, UFCMAXGW k is the maximum gross weight of non-capsule UFC k, UFCMAXVW k is the maximum bulk weight of non-capsule UFC k.
When a main multi-branch type order does not leave the package cabin and the current order is assembled with other orders, the constraint condition of the objective function is as follows:
When a main multi-branch type order does not go through the package cabin and the current order is assembled with other orders, namely when Y ik＝1,Zij =1, the constraint condition of the objective function is as follows:
Where Y ik = 1 indicates that an order of primary multi-type i leaves non-package UFC k,Zij = 1 indicates that orders i and j are pieced together, OB (OP i) is the originating port of an order of primary multi-type i, OB (OP j) is the originating port of an order of primary multi-type j, OB (DP i) is the destination port of an order of primary multi-type i, OB (DP j) is the destination port of an order of primary multi-type j, OB (EETD i) is the earliest take-off time of an order of primary multi-type i, OB (LETD i) is the latest take-off time of an order of primary multi-type i, OB (LETD j) is the latest take-off time of an order of primary multi-type j, MAWBCW i is GW j is the gross weight of an order of primary multi-type j, and VW j is the volumetric weight of an order of primary multi-type j.
The construction process of the constraint condition of the present invention is further described below with reference to specific examples:
1. And judging whether the current order leaves the capsule or not, and the capsule on which flight date to leave.
The set of orders for a master order or a master part OA i and the set of pods is FC { FC 1,FC2,…,FCL }. And (3) capsule: the air freight generation is signed by the aviation department to take out the mode of fixing the freight quantity with specific weight on each flight on the aviation department.
X ik = 0 or 1 (1 denotes the current order i parcel k), i = 1,2, …, M, k = 1,2, …
101. One order can only be put into one capsule, and is not split into 2 capsules.
(Indicating that the current order i can only travel 1 capsule k and cannot be split into multiple capsules)
For a main multi-point order set OB i, the same is done.
102. The origin and destination ports of the order are equal to the origin and destination ports of the package;
For the master order or a master one-part order set OA i,
OA (OP i)＝FC(FCOPk), if X ik =1
OA (DP i)＝FC(FCDPk), if X ik =1
For a main multi-point order set OB i, the same is done.
103. The earliest take-off time and the latest take-off time of the order comprise the take-off time of the package cabin flight;
OA (EETD i)<＝FC(FCETDk), if X ik =1
OA (LETD i)>＝FC(FCETDk), if X ik =1
For a main multi-point order set OB i, the same is done.
104. The sum of the volume weights of the orders of the walking capsule is lower than the maximum gross weight of the capsule;
105. the sum of the gross weights of the orders going through the capsule is lower than the maximum bulk weight of the capsule
For a main order, a main order and a multi-order, the bag cabin is transported, and the bag cabin transport cost is fixed, so that the leaning grade of the main order is not needed to be considered, and bubbles are eaten;
2. judging whether the current order leaves the package cabin or not, and when the current order leaves the flight, judging which flight date to leave
The set of orders for a master order or a master part OA i and non-package is UFC { UFC 1,UFC2,…,UFCW }.
Y ik =0 or 1 (1 denotes that the current order i walks away from the non-package k), i=1, 2, …, M, k=1, 2, …, W
201. An order can only go to a non-deck or a flight of a deck, and cannot walk both the deck and the non-deck at the same time.
(Meaning that the current order i can only travel 1 pod or 1 non-pod k, and cannot be split into multiple non-pods).
202. An order can only be up to a flight other than the cabin, and is not split into 2 flights.
(Meaning that the current order i can only travel 1 non-capsule k and cannot be split into multiple non-capsules).
For a main multi-point order set OB i, the same is done.
203. The origin and destination ports of the order are equal to the origin and destination ports of the package;
For the master order or a master one-part order set OA i,
OA (OP i)＝UFC(UFCOPk), if Y ik =1
OA (DP i)＝UFC(UFCDPk), if Y ik =1
For a main multi-point order set OB i, the same is done.
204. The earliest take-off time and the latest take-off time of the order comprise the take-off time of the package cabin flight;
OA (EETD i)<＝UFC(UFCETDk), if Y ik =1
OA (LETD i)>＝UFC(UFCETDk), if Y ik =1
For a main multi-point order set OB i, the same is done.
205. The sum of the volume weights of the orders walking the non-capsule is lower than the maximum gross weight of the non-capsule;
206. the sum of the gross weights of the orders traveling non-capsule is lower than the maximum bulk weight of the non-capsule
For a main one-to-one and straight list set OA, the leaning level of the main list is considered. A main multi-point order set OB needs to consider the leaning grade and the spelling of the main order. Leaning stage: the air freight rates are divided into freight rates of different weight levels of M, N,45,100,300,500, and if the freight rate of a weight level multiplied by the lowest weight of the weight level is lower than the product of the actual weight multiplied by the freight rate of the corresponding level, the carrier can bill and declare the weight according to the lowest weight of the weight level. For example, a 100 kg grade rate of 1,300 kg grade rate of 0.9, if 299 kg of goods, 299 x 1 being greater than 300 x 0.9, the carrier may weigh the goods 300 (rather than 299) and run the 300 kg grade rate, thus resulting in a lower overall rate. Assembling and eating a bubble: the air cargo is multiplied by 1000 and divided by 6 to obtain the volume weight (kilogram) according to the volume (cubic meter), if the volume weight is higher than the gross weight, the gross weight is used as the charging weight according to the volume weight as the bubble cargo, otherwise, the gross weight is used 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 bills and the sum of the volume weights of all the bills through the matching of the bubble cargo and the heavy cargo.
2.1, The current main multi-point order OB does not go through the package cabin, and the current order and other orders are assembled together.
If Y ik =1 (1 indicates that the order i of the previous prime multi-split walks to non-capsule k), i=1, 2, …, N, k=1, 2, …, W,
Z ij = 0 or 1 (1 denotes that orders i and j are pieced together), i = 1,2, …, N, j = 1,2, …, N,
2.1.1 The origin and destination ports of the assembled order are equal;
OB (OP i)＝OB(OPj), if Y ij =1
OB (DP i)＝OB(DPj), if Y ij =1
2.1.2 The earliest take-off time and the latest take-off time of the assembled order are intersected;
{ OB (EETD i),OB(LETDi)}∩{OB(EETDj),OB(LETDj) } is-! Null, if Y ij =1
2.2 Weight grade of Main sheet
For a set of primary multi-split orders OB, if Y ik =1 (1 indicates that the current primary multi-split order i goes to non-package k), i=1, 2, …, N, k=1, 2, …, W,
Z ij =0 or 1 (1 denotes that orders i and j are pieced together), i=1, 2, …, N, j=1, 2, …, N, and the current non-capsule order OB i corresponds to a billing weight of
The first branch represents that if the order and other orders are spelled into a main order, the sum of gross weights and the sum of volume weights of the orders are compared, and a large value is used as the charging weight of the main order
The business meaning of the second branch is that if the current order has been assembled with the previous order into a master order, the master order is charged again without repeated calculation.
The function F is defined as a function of the freight of the current main bill after the main bill is charged again and the freight of the flight is charged.
F(MAWBCWi,RCCPj)＝min{MAWBCWi*FRCCPj(MAWBCWi)，
min(ceil(RCj(MAWBCWi)),FRCCPj(ceil(RCj(MAWBCWi)))}
i＝1，2，...，N，j＝1，2，...，W
The charging re-reliability level function RC is defined to give a charging re-weight, returning a kg level below the current charging re-weight and maximum.
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 RCCPk＝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
A billing re-freight function FRCCP is defined to give a billing re-freight, return a freight rate applicable to the current billing re-freight, and the set that the function can return is RCCP.
The charging re-reliability level adjustment function ceil is defined as the lowest kilogram level greater than the current charging re-weight.
MAWBCW i*RC(MAWBCWi)＞ceil(MAWBCWi)*RC(ceil(MAWBCWi), MAWBCW i＝ceil(MAWBCWi).
For example, 299 corresponds to a kilogram grade rate of 100 rates (1 yuan per kilogram), greater than 299 and the lowest kilogram grade of 300, 300 rates of 0.9 yuan per kilogram.
The principle is the same for a main one-to-one and straight one set OA.
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, the optimization process needs to be solved by a simulated annealing algorithm. The solving process is as follows:
the initial temperature t=t max is set,
The solution for each order is defined by three values: the capsule of which flight date to walk, the non-capsule of which flight date to walk (these 2 mutex), and those orders are configured as a master order.
The origin and destination ports initially resolved to orders are defined to be equal to the origin and destination ports of the package, and the flight date and time is the earliest of the flights. The aggregate is accumulated up until the aggregate volume or weight of orders for the cabin to cabin flights exceeds 80% of the maximum volume or weight (experience). The next earliest capsule flight on date and time is then taken. The cycle is continued until all cabin flights exceed 80% of the maximum volume or weight (empirical value).
The remaining orders then travel to the origin and destination ports of the order equal to the origin and destination ports of the non-package, and the flight date and time is the earliest of the flights. The aggregate volume or weight of orders for the booked to non-booked flights is accumulated up until 80% of the maximum volume or weight is exceeded (empirical value). The next earliest non-pod flight on date and time is then taken, continuing the change process.
If the number is a main multi-score, the same flight date is a main list.
Before initialization, the order is ordered from big to small according to the latest take-off time of the original port, the destination port and the flights of the order (the order of the goods with big weight is prioritized, and the earlier flights are ordered), and then the initialization is carried out. The set of initial solutions r is initialized by the above procedure.
Internal circulation
Randomly selecting a solution r t from the neighborhood of r, calculating the values of the objective function E corresponding to r and r t, and if the objective function value corresponding to r t is smaller, making r=r t; otherwise if not
Let r=r t.
The neighborhood of r is constructed in such a way that the following 2 sets of random i-th valid values (the following sets may have N validity periods, the system generates a random number Y of 1 to N according to N, and then fetches the i-th valid value according to the random number Y):
the origin port and destination port of the order are equal to the origin port and destination port of the capsule, the capsule has the rest of the capsule which can encase the weight and volume of the order, and the flight date is smaller than the earliest take-off time of the order and larger than the latest take-off time of the order.
The origin and destination ports of the order are equal to those of the non-package and the non-package has a remaining space thereon that encloses the weight and volume of the order, and the date of the flight is less than the earliest departure time of the order and greater than the latest departure time of the order.
If the internal circulation stop condition (1. Mean value of objective function E is stable 2. Target value change of several continuous steps is small 3. Fixed sampling step number) is not satisfied, repeating the previous external circulation
Cooling t=decease (t)
If the external circulation stopping condition is not met, turning to the second step (1. Reaching the end temperature 2. Reaching the iteration number 3. Keeping the optimal value unchanged for a plurality of steps continuously); otherwise the algorithm ends.
According to the invention, the objective function is constructed by taking the lowest order freight cost of the floating bunk as the objective, and the objective function is solved by using the simulated annealing algorithm to obtain the air freight mode, so that the freight cost can be reduced to the greatest extent.
The invention also provides an implementation method of intelligent air freight stowage, which comprises the following steps:
The order data acquisition module is used for acquiring order data in the air freight transportation process;
the objective function construction module is used for constructing an objective function by taking the lowest cost of the order freight of the floating bunk as the objective;
The constraint condition determining module is used for determining the constraint condition 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 intelligent air freight loading provided by the invention are the same as those of the implementation method for intelligent air freight loading described in the technical scheme, and are not repeated here.
The embodiment of the invention also provides electronic equipment, 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 respectively connected through the bus, and when the computer program is executed by the processor, the processes of the embodiment in the implementation method for intelligent allocation of air freight can be realized, and the same technical effects can be achieved, so that repetition is avoided and redundant description is omitted.
In addition, the embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, the computer program when executed by a processor realizes each process in the embodiment of the implementation method of intelligent loading of air freight, and the same technical effects can be achieved, so that repetition is avoided, and the description is omitted here.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art can easily think about variations or alternatives within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. The implementation method of the intelligent allocation of the air freight is characterized by comprising the following steps:
Step 1: acquiring order data in the air freight transportation process;
step 2: constructing an objective function by taking the lowest order freight cost of the floating bunk as a target;
The objective function in the step 2 is as follows:
Wherein N is the number of orders of a main multi-branch type, M is the number of orders of a straight order or a main one-branch type, F (MAWBCW i,RCCPj) is the cost of the orders of a main multi-branch type, and F (MAWBCW k,RCCPj) is the cost of the orders of a straight order or a main one-branch type;
Step 3: determining constraint conditions of the objective function according to the freight type and the flight date of each order;
The step 3: determining constraints of the objective function according to the freight type and the flight date of each order, including:
when the order is a straight order or a main one-branch type order is a parcel cabin, the constraint condition of the objective function is as follows:
Wherein the set of straight order or one-main-one-part order is OA i, the set of package is FC { FC 1,FC2,…,FCL},Xik =0 or 1,1 indicates that the straight order or one-main-one-part order i walks the package FC k, 0 indicates that the straight order or one-main-one-part order i does not walk the package FC k, and i=1, 2, …, M, k=1, 2, …, L, OA (OP i) is the origin port of the straight order or one-main-one-part order i, FC (FCOP k) is the origin port of the package FC k, OA (DP i) is the destination port of the straight order or one-main-one-part order i, FC (FCDP k) is the destination port of the package FC k, OA (EETD i) is the earliest take-off time of a straight order or a primary one-part order i, FC (FCETD k) is the take-off time of a capsule FC k, OA (LETD i) is the latest take-off time of a straight order or a primary one-part order i, OA (GW i) is the gross weight of a primary order or a primary one-part order j, OB (GW i) is the gross weight of a primary one-part order i, FCMAXGW k is the maximum gross weight of a capsule FC k, OA (VW i) is the bulk weight of a primary order or a primary one-part order j, OB (VW i) is the maximum bulk weight of a capsule FC k;
step 4: and solving the objective function to obtain the air freight mode with the lowest cost.
2. The method for implementing intelligent allocation of air freight according to claim 1, wherein the step 3: determining constraints of the objective function according to the freight type and the flight date of each order, and further comprising:
when the order of the straight order or the main one-branch type does not go through the package cabin, the constraint condition of the objective function is as follows:
Wherein the collection of non-capsule is UFC { UFC 1,UFC2,…,UFCW},Yik =0 or 1,1 indicates that current order i walks non-capsule UFC k, 0 indicates that current order i does not walk non-capsule UFC k,k＝1,2,…,W,UFC(UFCOPk) is the originating port of non-capsule UFC k, UFC (UFCDP k) is the originating port of non-capsule UFC k, UFC (UFCETD k) is the takeoff time of non-capsule UFC k, UFCMAXGW k is the maximum gross weight of non-capsule UFC k, UFCMAXVW k is the maximum bulk weight of non-capsule UFC k.
3. The method for implementing intelligent allocation of air freight according to claim 2, wherein the step 3: determining constraints of the objective function according to the freight type and the flight date of each order, and further comprising:
When a main multi-branch type order does not go through the package cabin and the current order is assembled with other orders, namely when Y ik＝1,Zij =1, the constraint condition of the objective function is as follows:
Where Y ik = 1 indicates that an order of primary multi-type i leaves non-package UFC k,Zij = 1 indicates that orders i and j are pieced together, OB (OP i) is the originating port of an order of primary multi-type i, OB (OP j) is the originating port of an order of primary multi-type j, OB (DP i) is the destination port of an order of primary multi-type i, OB (DP j) is the destination port of an order of primary multi-type j, OB (EETD i) is the earliest take-off time of an order of primary multi-type i, OB (LETD i) is the latest take-off time of an order of primary multi-type i, OB (LETD EETD j) is the earliest take-off time of an order of primary multi-type j, OB (LETD j) is the latest take-off time of an order of primary multi-type j, GW 28 is the gross weight of an order of primary multi-type j, and VW j is the volumetric weight of an order of primary multi-type j.
4. The method for implementing intelligent allocation of air freight according to claim 3, wherein when a main multi-classification order does not go through the capsule and the current order is assembled with other orders, the charging mode of the objective function for the main multi-classification order is as follows:
Wherein Y ik =1, 1 indicates that the current main multi-split order i leaves non-package k, i=1, 2, …, N, k=1, 2, …, W, is the number of non-package, Z ij =0 or 1,1 indicates that orders i and j are pieced together, 0 indicates that orders i and j are not pieced together, i=1, 2, …, N, j=1, 2, …, N, FRCCP j is a billing re-freight rate function, ceil is a billing re-stage adjustment function, and RC j is a billing re-stage function.
5. The implementation method of the intelligent allocation of the air freight is characterized by comprising the following steps:
The order data acquisition module is used for acquiring order data in the air freight transportation process;
the objective function construction module is used for constructing an objective function by taking the lowest cost of the order freight of the floating bunk as the objective;
the objective function is:
Wherein N is the number of orders of a main multi-branch type, M is the number of orders of a straight order or a main one-branch type, F (MAWBCW i,RCCPj) is the cost of the orders of a main multi-branch type, and F (MAWBCW k,RCCPj) is the cost of the orders of a straight order or a main one-branch type;
The constraint condition determining module is used for determining the constraint condition of the objective function according to the freight type and the flight date of each order;
the determining constraint conditions of the objective function according to the freight type and the flight date of each order comprises the following steps:
when the order is a straight order or a main one-branch type order is a parcel cabin, the constraint condition of the objective function is as follows:
Wherein the set of straight order or one-main-one-part order is OA i, the set of package is FC { FC 1,FC2,…,FCL},Xik =0 or 1,1 indicates that the straight order or one-main-one-part order i walks the package FC k, 0 indicates that the straight order or one-main-one-part order i does not walk the package FC k, and i=1, 2, …, M, k=1, 2, …, L, OA (OP i) is the origin port of the straight order or one-main-one-part order i, FC (FCOP k) is the origin port of the package FC k, OA (DP i) is the destination port of the straight order or one-main-one-part order i, FC (FCDP k) is the destination port of the package FC k, OA (EETD i) is the earliest take-off time of a straight order or a primary one-part order i, FC (FCETD k) is the take-off time of a capsule FC k, OA (LETD i) is the latest take-off time of a straight order or a primary one-part order i, OA (GW i) is the gross weight of a primary order or a primary one-part order j, OB (GW i) is the gross weight of a primary one-part order i, FCMAXGW k is the maximum gross weight of a capsule FC k, OA (VW i) is the bulk weight of a primary order or a primary one-part order j, OB (VW i) is the maximum bulk weight of a capsule FC k;
And the objective function solving module is used for solving the objective function to obtain the air freight mode with the lowest cost.
6. An electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected by the bus, characterized in that 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 4.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of a method for implementing intelligent stowage of air cargo according to any of claims 1 to 4.
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