CN116681151A - Packing optimization method based on combined stacking and lowest horizontal line - Google Patents
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Abstract
The invention relates to the technical field of boxing problem optimization, in particular to a boxing optimization method based on combined stacking and a lowest horizontal line, which comprises the following steps of: s1, sorting cargoes in groups according to loading attributes of the cargoes; s2, based on a combined stacking algorithm, carrying out combined stacking on cargoes according to a grouping and sorting sequence to obtain a cargo stacking set; s3, processing the cargo stacking set in a three-dimensional space based on a rectangular-in-rectangular layout algorithm of the lowest horizontal line to obtain a cargo boxing sequence, optimizing the cargo boxing sequence by using a simulated annealing algorithm, and outputting a boxing optimal scheme; and S4, determining the loading position of the goods in the three-dimensional space according to the optimal boxing scheme, and boxing. According to the invention, the problem scale is reduced by utilizing the combined stacking model to optimize the boxing space and sequence of each truck one by one, so that the problem can find high-quality solutions in a short time, and the efficiency of the boxing process is improved.
Description
Technical Field
The invention relates to the technical field of boxing problem optimization, in particular to a boxing optimization method based on combined stacking and a lowest horizontal line.
Background
The problem of three-dimensional packing optimization widely exists in the storage industry of goods in a warehouse, the packing industry of containers in ports, the loading industry of goods in trucks and the like. This problem is widely present in the following production scenarios:
1. in the goods storage of warehouse, the enterprise needs to deposit goods in different subregions according to the timeliness and the storage cost of goods, and the commodity circulation dispatch of being convenient for reduces inventory cost, improves production efficiency.
2. In port container boxing, enterprises need to consider the multi-constraint cargo boxing such as the center of gravity of a ship body, stock time and the like, and the purpose is to ensure the transportation safety and simultaneously maximize the space utilization rate of the container.
3. In the loading of trucks, businesses need to stack and then bin the same type of cargo in order to maximize cargo loading and unloading efficiency.
In the above scenario, there are many limitations to cargo transportation, such as: often, multiple delivery points and different kinds of goods are involved in truck transportation, and in order to improve space utilization, a cargo loading sequence and a cargo stacking mode need to be reasonably planned; the load bearing constraint of the goods is also considered in truck transportation, so that the goods are prevented from being damaged in the transportation process, and meanwhile, in order to prevent the goods from overturning during braking, the front part of the goods needs to be resisted; container cargo loading also requires consideration of cargo center of gravity distribution. In the face of multiple loading constraints and large-scale cargo quantities, unreasonable scheduling strategies not only reduce production efficiency, but also create significant profit losses.
The three-dimensional packing problem is a combinatorial optimization problem. For large logistics enterprises, logistics transportation often involves multiple supply points and different kinds of cargoes, and further needs to consider a plurality of constraints such as cargo bearing constraint, volume constraint, loading sequence constraint, cargo nesting combination constraint, cargo resisting constraint and the like. The existing three-dimensional boxing algorithm does not consider the practical constraint, and the problems that the gravity center of the goods is unstable and overturns, the truck is overweight, the load of the goods is overlarge and the goods are damaged are caused in practical application. In addition, due to the fact that goods are various, the quantity of goods is large in scale, the combination optimization difficulty is greatly improved, the time complexity is rapidly increased along with the increase of the problem scale, manual calculation is particularly difficult, time is long, and the effect is poor.
Disclosure of Invention
The invention aims to solve the technical problems that the combination mode is difficult to optimize and the complexity is high because the limitation of cargo bearing constraint, volume constraint and the like is not considered when the cargo stack is reprocessed in the prior art.
In order to solve the technical problems, the embodiment of the invention provides a boxing optimization method based on combined stacking and a lowest horizontal line, which comprises the following steps:
s1, sorting cargoes in groups according to loading attributes of the cargoes;
s2, based on a combined stacking algorithm, carrying out combined stacking on the cargoes according to a grouping and sorting sequence to obtain a cargo stacking set;
s3, processing the goods stacking set in a three-dimensional space based on a rectangular layout algorithm in a rectangle of a lowest horizontal line to obtain a goods boxing sequence, optimizing the goods boxing sequence by using a simulated annealing algorithm, and outputting a boxing optimal scheme;
and S4, determining the loading position of the goods in the three-dimensional space according to the optimal boxing scheme, and boxing.
Further, the loading attributes of the cargo include:
cargo length l i Width w of goods i Height h of goods i Cargo mass m i Height eh of nesting of goods i Direction of rotation R of goods i Order of loading goods O i Type N of goods i Variable a of whether goods are used for stacking i Maximum load bearing of goods
Still further, the stack set of goods has the following properties:
length of stack L j Width of stack W j Stacking height H j Stacking mass M j The quantity K of goods contained in the stack j 。
Still further, the combined stacking algorithm satisfies:
obj：
s.t.
still further, the intra-rectangle layout algorithm satisfies:
obj：
s.t.
a i x i +l i ≤L i＝1，…，n (1)
a i y i +w i ≤W i＝1，…，n (2)
a i x i ＜a j x j i, j=1, …, n and O i ＞O j (5)
O i ＞O j i, j=1, …, n and i+.j (6)
Wherein the three-dimensional space has a length L and a width W, and the number of the goods stacking sets is n and x i Representing the x coordinate, y of the i-th lower left corner of the stack set of goods relative to the origin of the three-dimensional space i Representing the y-coordinate of the bottom left corner of the ith stack of goods relative to the origin of the three-dimensional space i Representing the weight of the ith cargo, volume i Representing the volume of the ith cargo, maxWeight j Representing the maximum allowable load bearing of the j-th three-dimensional space.
Still further, step S3 comprises the sub-steps of:
s31, taking all the goods stacking sets as a loading list, and creating an empty loading sequence as an optimal solution;
s32, selecting one cargo stack set from the loading list to load in the three-dimensional space, initializing a lowest horizontal line according to the cargo stack set, and simultaneously updating the loading sequence;
s33, repeating the step S32 until the loading list is empty or the three-dimensional space cannot be reloaded with any goods stacking set;
s34, disturbing the loaded goods stacking set in the three-dimensional space based on the simulated annealing algorithm, and updating the optimal solution;
and S35, iterating to the step 32 for execution until the optimal solution meets a preset iteration target, and outputting the loading sequence corresponding to the optimal solution.
Further, in step S32, a step of selecting one of the cargo stacking sets from the loading list to load in the three-dimensional space is specifically:
and selecting the goods stacking set with the highest score and meeting the position feasibility constraint from the loading list for loading.
Further, in step S32, the step of initializing the lowest horizontal line according to the stack set of goods is specifically:
initializing the lowest horizontal line with the origin of the three-dimensional space, the lowest horizontal line having a starting point (0,w) i ) Width (W-W) i ) The direction is the y-axis direction;
and merging the sides of the stack combination with the smallest x coordinate and adjacent to the sides parallel to the y axis when the lowest horizontal line cannot accommodate any one of the stack combinations.
Further, based on the simulated annealing algorithm, the step of perturbing the loaded stack set of goods in the three-dimensional space and updating the optimal solution comprises the sub-steps of:
s351, calculating a first function solution by using the simulated annealing algorithm with the loading sequence as an initial solution, to obtain an objective function value f (old), and then initializing a variable parthennum=0 for the simulated annealing algorithm, an initialization temperature T and an isothermal iteration number l:
s352, exchanging the loaded goods stacking set with the unloaded goods stacking set, and calculating a second function solution to obtain a second function value f (new);
s353, judging whether f (new) is smaller than f (old), if yes, proceeding to step S314; if not, go to step 315;
s354, replacing the first functional solution with the second functional solution, updating f (old) to f (new), and then executing step S315;
s355, accepting a differential solution by using a Metropolis criterion;
s356, judging whether the iteration times reach isothermal iteration times l, if not, adding 1 to the iteration times, and returning to the step S352; if yes, go to step S357;
s357, judging whether the temperature T reaches the end temperature or whether the parthennum reaches the set tolerance times, if not, subtracting 1 from the temperature T, and returning to the step S351; if yes, outputting the current second function solution as the optimal boxing scheme.
Still further, in step S316, the metrapidis criterion satisfies:
Δf＝f(newSolution)-f(oldSolution)
the invention has the beneficial effects that the method for optimizing the boxing based on the combined stacking and the lowest horizontal line, which considers the loading constraint, can be conveniently realized by the existing computer equipment, reduces the workload of manually arranging cargoes into trucks, and reduces the time loss; meanwhile, the problem size is reduced by utilizing the combined stacking model to optimize the boxing space and sequence of each truck one by one, so that the problem can find high-quality solutions in a short time, and the efficiency of the boxing process is improved.
Drawings
FIG. 1 is a schematic flow chart of steps of a method for optimizing packing based on combined stacking and lowest horizon according to an embodiment of the present invention;
FIG. 2 is a schematic illustration of the nesting height of a stack set of goods according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a stacking process provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of a stacking and gathering location of goods according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of minimum horizontal line generation provided by an embodiment of the present invention;
fig. 6 is a schematic diagram of minimum horizontal line merging provided in an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic step flow diagram of a method for optimizing boxing based on combined stacking and a lowest horizontal line, which includes the following steps:
s1, sorting cargoes in groups according to loading attributes of the cargoes.
The embodiment of the invention defines the following problems for the case filling:
the goods stacking set is as follows: giving n cuboid-like cargoes, stacking cargoes of the same kind, and packaging to form a whole;
the goods are of the following types: in the process of packing cargoes into a collection of cargoes stacks, defining which cargoes can be packed into the same stack, and cargoes of the same kind have the same length and width;
the height of the goods nest is as follows: in the process of packing rectangular cargoes into stacks, the shape of part of cargoes is non-rectangular, and two adjacent cargoes can be nested when stacking, wherein the stacked height is called a nesting height.
The boxing problem is as follows: given a cargo list K with the number of n and an unlimited number of trucks, packing the stackable and identical cargoes in K into a set of m cargo stacks, and loading all the m stacks into three-position-Buddha keys of the trucks; the goal is to find a tote solution based on the loading and unloading order of the different stacks and the weight constraints of the trucks, minimizing the number of trucks used and the factory inventory due to the early delivery.
Further, the loading attributes of the cargo include:
cargo length l i Width w of goods i Height h of goods i Cargo mass m i Height eh of nesting of goods i Direction of rotation R of goods i Order of loading goods O i Type N of goods i Variable a of whether goods are used for stacking i Maximum load bearing of goods
Still further, the stack set of goods has the following properties:
length of stack L i Width of stack W j Stacking height H j Stacking mass M j The quantity K of goods contained in the stack j 。
Specifically, in the embodiment of the invention, the stacking length is any cargo length contained in the stacking machine, the stacking width is any cargo width contained in the stacking machine, the stacking height is the sum of all cargo heights contained in the stacking machine minus the sum of nesting heights of adjacent cargoes, and the stacking quality is the sum of all cargo qualities contained in the stacking machine.
S2, based on a combined stacking algorithm, carrying out combined stacking on the cargoes according to a grouping and sorting sequence to obtain a cargo stacking set.
In an embodiment of the present invention, the combined stacking algorithm is used to: given n cuboids and a maximum height H, the geometry of each cuboid is l i ×w i ×h i (i=1, 2, …, n) it is necessary to determine that these cuboids are stacked in combination into m stacks without exceeding the maximum height, each stack containing k cuboids of size L j ×W j ×H j So that the resulting stack height is as close as possible to the maximum height, i.e. the average loading rate of the stacks is maximum.
Still further, the combined stacking algorithm satisfies:
obj：
s.t.
wherein the objective function represents that the average value of the ratio of the height to the maximum height of all stacks is the largest; constraint (1) means that the height of all stacks must be less than the maximum height; constraint (2) represents the maximum load bearing of a certain cargo in the stackShould be greater than the sum of the cargo masses above it; constraint (3) specifies the succession of loading sequences; constraint (4) defines alpha i A zero-variable indicates whether the ith shipment is added to the current stack, and a 1 indicates that the ith shipment is included in the current stack with other shipments.
Specifically, in the embodiment of the invention, when combined stacking and layout is performed, cuboids of the same type have the same length and width, and only the height limitation, the loading sequence and the quality constraint need to be considered at the moment. When combining the cuboids, taking natural gravity into consideration, directly taking out the first cuboid in the cuboid list and adding the first cuboid into the bottom of the stack, then searching the remaining cuboid list for the cuboid, and adding the cuboid into the corresponding stack when the loading sequence is not more than the cuboid taken out before the first cuboid is satisfied, and the bottom cuboid can bear the newly added cuboid mass and the stacking height is not more than the maximum height. If the cuboid list is traversed and then the cuboid list does not meet the conditions, a stack is directly formed.
Referring to fig. 2, fig. 2 is a schematic diagram illustrating a nesting height of a stacking set of cargos, wherein a cargo 1 is packed on a cargo 2, and the overall height is h 1 +h 2 -eh 1 。
The stacking process is shown in fig. 3.
And S3, processing the goods stacking set in a three-dimensional space based on a rectangular layout algorithm in a rectangle of the lowest horizontal line to obtain a goods boxing sequence, optimizing the goods boxing sequence by using a simulated annealing algorithm, and outputting a boxing optimal scheme.
Specifically, in the embodiment of the invention, the position of each cargo in the z-axis direction can be determined by combining the stacking algorithm, and as the cargoes in the same stack have the same length and width, the x-coordinate and the y-coordinate of the stack can be continuously determined. In the top view, the three-dimensional boxing problem is simplified into a two-dimensional rectangular internal loading rectangular layout problem. A rectangle may be used to represent a stack and a container may be used to represent the three-dimensional space of the loading truck.
The rectangle-in-rectangle layout algorithm is used for selecting some rectangles from the n rectangles of the cargo stacking combination to be loaded into the three-dimensional space, so that the sum of the loaded rectangular areas is maximum.
Still further, the intra-rectangle layout algorithm satisfies:
obj：
s.t.
a i x i +l i ≤L i＝1，…，n (1)
a i y i +w i ≤W i＝1，…，n (2)
a i x i ＜a j x j i, j=1, …, n and O i ＞O j (5)
O i ＞O j i, j=1, …, n and i+.j (6)
Wherein the three-dimensional space has a length L and a width W, and the number of the goods stacking sets is n and x i Representing the x coordinate, y of the i-th lower left corner of the stack set of goods relative to the origin of the three-dimensional space i Representing the y-coordinate of the bottom left corner of the ith stack of goods relative to the origin of the three-dimensional space i Representing the weight of the ith cargo, volume i Representing the volume of the ith cargo, maxWeight j Representing the maximum allowable load bearing of the j-th three-dimensional space.
Of the above constraints, constraint (1) and constraint (2) define the range of values of x-coordinate and y-coordinate, (x) i ，y i ) The lower left corner coordinate of the ith rectangle is referred to, so that the small rectangle is ensured to be positioned in the rectangular container; constraint (3) and constraint (4) constrain the area between two rectangles that would not overlap if both rectangles were loaded into a circular container; constraint (5) specifies that any stack must be adjacent to another stack to the left of the x-axis, or if there is a single stack in the truck, the only stack should be placed in front of the truck. As shown in fig. 4, stacks a and B are inhibited from being placed, allowing all other stacks to be placed; constraint (6) constraint that stacks with a large loading order should be loaded preferentially; the constraint (7) constrains the total weight of the truck-loaded stack not to exceed the maximum load-bearing capacity of the loading truck.
Still further, step S3 comprises the sub-steps of:
s31, taking all the goods stacking sets as a loading list, and creating an empty loading sequence as an optimal solution;
s32, selecting one cargo stack set from the loading list to load in the three-dimensional space, initializing a lowest horizontal line according to the cargo stack set, and simultaneously updating the loading sequence;
s33, repeating the step S32 until the loading list is empty or the three-dimensional space cannot be reloaded with any goods stacking set;
s34, disturbing the loaded goods stacking set in the three-dimensional space based on the simulated annealing algorithm, and updating the optimal solution;
and S35, iterating to the step 32 for execution until the optimal solution meets a preset iteration target, and outputting the loading sequence corresponding to the optimal solution.
Further, in step S32, a step of selecting one of the cargo stacking sets from the loading list to load in the three-dimensional space is specifically:
and selecting the goods stacking set with the highest score and meeting the position feasibility constraint from the loading list for loading.
Specifically, the proper rectangle is selected through the detection of the high-low and position feasibility of the rectangle scoring, and the scoring formula is as follows:
wherein the width and height of the rectangle are used as the scoring of the similarity, if the height is higher as the scoring of the similarity, the rectangle is subjected to rotation processing, and when the scores of the two rectangles are the same, the rectangle which is ranked earlier in the sequence is preferentially selected for placement.
Since the scoring mechanism only scores the matching degree of the side width and line of the rectangle, and the rectangle length is not considered, which may cause the rectangle to be loaded to exceed the limit of the rectangular container, the selected rectangle needs to be checked to be a proper rectangle through the constraint (1) and the constraint (2) in the rectangle layout algorithm in the rectangle, and if the rectangle does not meet the constraint at this time, the rectangle is moved to the end of the list to reselect a proper rectangle. The above process is repeated until the rectangular container is filled, and an initial solution for the cargo load is obtained.
Further, in step S32, the step of initializing the lowest horizontal line according to the stack set of goods is specifically:
initializing the lowest horizontal line with the origin of the three-dimensional space, the lowest horizontal line having a starting point (0,w) i ) Width (W-W) i ) The direction is the y-axis direction;
and merging the sides of the stack combination with the smallest x coordinate and adjacent to the sides parallel to the y axis when the lowest horizontal line cannot accommodate any one of the stack combinations.
Specifically, referring to fig. 5, fig. 5 is a schematic diagram of generating a minimum horizontal line according to an embodiment of the present invention, according to a stacking loading sequence and maximizing a rectangular container utilization area, a lower left corner of a rectangle is placed initially coincident with an origin of the rectangular container, a lower left corner coordinate of the rectangle is (0, 0), and for convenience of updating the minimum horizontal line, an algorithm adopts the lower left corner coordinate of the rectangle, and an example of placement is shown in fig. 4. After loading the first rectangle, initializing the lowest horizontal line, which is line2, generates two line segments line1 and line2. The starting point of the line is (l) i 0), the width of the line is w i The second segment line2 starts at (0,w) i ) Width (W-W) i ). At this time, the x coordinate of the start point of line2 is the smallest based on the positive x-axis direction.
After the lowest horizontal line is generated, the proper rectangle is preferentially selected to be arranged on the lowest horizontal line. When the lowest horizontal line cannot accommodate any rectangle in the rectangle list, merging the lowest horizontal line with the adjacent line segments, and selecting the line segments with smaller adjacent starting points x coordinates for merging in order to maximize the utilization of the rectangular container area, wherein a merging schematic diagram is shown in fig. 6; if the x coordinate values of the starting points of two adjacent line segments are equal, the three lines are combined.
Further, based on the simulated annealing algorithm, the step of perturbing the loaded stack set of goods in the three-dimensional space and updating the optimal solution comprises the sub-steps of:
s351, calculating a first function solution by using the simulated annealing algorithm with the loading sequence as an initial solution, to obtain an objective function value f (old), and then initializing a variable parthennum=0 for the simulated annealing algorithm, an initialization temperature T and an isothermal iteration number l:
s352, exchanging the loaded goods stacking set with the unloaded goods stacking set, and calculating a second function solution to obtain a second function value f (new);
s353, judging whether f (new) is smaller than f (old), if yes, proceeding to step S314; if not, go to step 315;
s354, replacing the first functional solution with the second functional solution, updating f (old) to f (new), and then executing step S315;
s355, accepting a differential solution by using a Metropolis criterion;
s356, judging whether the iteration times reach isothermal iteration times l, if not, adding 1 to the iteration times, and returning to the step S352; if yes, go to step S357;
s357, judging whether the temperature T reaches the end temperature or whether the parthennum reaches the set tolerance times, if not, subtracting 1 from the temperature T, and returning to the step S351; if yes, outputting the current second function solution as the optimal boxing scheme.
Still further, in step S316, the metapolis criterion satisfies:
Δf＝f(newSolution)-f(oldSolution)
and S4, determining the loading position of the goods in the three-dimensional space according to the optimal boxing scheme, and boxing.
The invention has the beneficial effects that the method for optimizing the boxing based on the combined stacking and the lowest horizontal line, which considers the loading constraint, can be conveniently realized by the existing computer equipment, reduces the workload of manually arranging cargoes into trucks, and reduces the time loss; meanwhile, the problem size is reduced by utilizing the combined stacking model to optimize the boxing space and sequence of each truck one by one, so that the problem can find high-quality solutions in a short time, and the efficiency of the boxing process is improved.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
While the embodiments of the present invention have been illustrated and described in connection with the drawings, what is presently considered to be the most practical and preferred embodiments of the invention, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various equivalent modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. A method of optimizing boxing based on combining stacks with a minimum horizon, the method comprising the steps of:
s1, sorting cargoes in groups according to loading attributes of the cargoes;
s2, based on a combined stacking algorithm, carrying out combined stacking on the cargoes according to a grouping and sorting sequence to obtain a cargo stacking set;
s3, processing the goods stacking set in a three-dimensional space based on a rectangular layout algorithm in a rectangle of a lowest horizontal line to obtain a goods boxing sequence, optimizing the goods boxing sequence by using a simulated annealing algorithm, and outputting a boxing optimal scheme;
and S4, determining the loading position of the goods in the three-dimensional space according to the optimal boxing scheme, and boxing.
2. The method of combined stacking and minimum level based bin optimization of claim 1 wherein the loading attributes of the cargo include:
cargo length l i Width w of goods i Height h of goods i Cargo mass m i Height eh of nesting of goods i Direction of rotation R of goods i Order of loading goods O i Type N of goods i Variable a of whether goods are used for stacking i Maximum load bearing of goods
3. The method of combined stacking and lowest horizon based boxing optimization of claim 2 wherein the set of stacks of goods has the following properties:
length of stack L j Width of stack W j Stacking height H j Stacking mass M j The quantity K of goods contained in the stack j 。
4. A combined stacking and lowest horizon based boxing optimization method in accordance with claim 3 wherein the combined stacking algorithm satisfies:
obj：
s.t.
5. the method of claim 4, wherein the rectangular-in-rectangular layout algorithm satisfies:
obj：
s.t.
a i x i +l i ≤L i＝1，…，n (1)
a i y i +w i ≤W i＝1，…，n (2)
a i x i ＜a j x j i, j=1, …, n and O i ＞O j (5)
O i ＞O j i, j=1, …, n and i+.j (6)
Wherein the three-dimensional space has a length L and a width W, and the number of the goods stacking sets is n and x i Representing the x coordinate, y of the i-th lower left corner of the stack set of goods relative to the origin of the three-dimensional space i Representing the y-coordinate of the bottom left corner of the ith stack of goods relative to the origin of the three-dimensional space i Representing the weight of the ith cargo, volume i Representing the volume of the ith cargo, maxWeight j Representing the maximum allowable load bearing of the j-th three-dimensional space.
6. The method of combined stacking and minimum level based bin optimization of claim 5, wherein step S3 comprises the sub-steps of:
s31, taking all the goods stacking sets as a loading list, and creating an empty loading sequence as an optimal solution;
s32, selecting one cargo stack set from the loading list to load in the three-dimensional space, initializing a lowest horizontal line according to the cargo stack set, and simultaneously updating the loading sequence;
s33, repeating the step S32 until the loading list is empty or the three-dimensional space cannot be reloaded with any goods stacking set;
s34, disturbing the loaded goods stacking set in the three-dimensional space based on the simulated annealing algorithm, and updating the optimal solution;
and S35, iterating to the step 32 for execution until the optimal solution meets a preset iteration target, and outputting the loading sequence corresponding to the optimal solution.
7. The method of claim 6, wherein in step S32, selecting one of the cargo stack sets from the loading list for loading in the three-dimensional space comprises:
and selecting the goods stacking set with the highest score and meeting the position feasibility constraint from the loading list for loading.
8. The method of claim 6, wherein the step of initializing the lowest horizon from the collection of stacks of goods in step S32 is:
initializing the lowest horizontal line with the origin of the three-dimensional space, the lowest horizontal line having a starting point (0,w) i ) Width (W-W) i ) The direction is the y-axis direction;
and merging the sides of the stack combination with the smallest x coordinate and adjacent to the sides parallel to the y axis when the lowest horizontal line cannot accommodate any one of the stack combinations.
9. The method of combined stacking and nadir level based bin optimization of claim 6 wherein the step of perturbing the loaded set of stacks of goods in the three-dimensional space based on the simulated annealing algorithm, updating the optimal solution comprises the sub-steps of:
s351, calculating a first function solution by using the simulated annealing algorithm with the loading sequence as an initial solution, to obtain an objective function value f (old), and then initializing a variable parthennum=0 for the simulated annealing algorithm, an initialization temperature T and an isothermal iteration number l:
s352, exchanging the loaded goods stacking set with the unloaded goods stacking set, and calculating a second function solution to obtain a second function value f (new);
s353, judging whether f (new) is smaller than f (old), if yes, proceeding to step S314; if not, go to step 315;
s354, replacing the first functional solution with the second functional solution, updating f (old) to f (new), and then executing step S315;
s355, accepting a differential solution by using a Metropolis criterion;
s356, judging whether the iteration times reach isothermal iteration times l, if not, adding 1 to the iteration times, and returning to the step S352; if yes, go to step S357;
s357, judging whether the temperature T reaches the end temperature or whether the parthennum reaches the set tolerance times, if not, subtracting 1 from the temperature T, and returning to the step S351; if yes, outputting the current second function solution as the optimal boxing scheme.
10. The method of optimizing truck cargo allocation taking into account cargo inventory costs according to claim 9, wherein in step S316, the metapliis criterion satisfies:
Δf＝f(newSolution)-f(oldSolution)
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