CN108846602A - A kind of logistics transportation dispatching method and device based on quantum fireworks algorithm - Google Patents

Abstract

The invention discloses a kind of logistics transportation dispatching methods based on quantum fireworks algorithm, by analyzing the Optimization Mechanism of fireworks algorithm and being directed to described logistics transportation scheduling problem, define fireworks population number in fireworks algorithm, the explosion parameters such as density and burst radius, devise the encoding and decoding strategy for dividing random by key in conjunction with vehicle route such as a kind of, the method for proposing a kind of quantum and the mutual inversion of phases of fireworks simultaneously, to introduce Quantum rotating gate enhancing algorithm ability of searching optimum, it is slow to solve the existing logistics transportation dispatching method speed of service, convergence capabilities are weak, and the technical problem that Searching efficiency is low.

Description

Logistics transportation scheduling method and device based on quantum firework algorithm

Technical Field

The invention relates to the field of logistics scheduling, in particular to a logistics transportation scheduling method and device based on a quantum firework algorithm.

Background

The logistics industry is internationally considered as the basic industry of national economic development, the development degree of the logistics industry is one of the important marks of the modernization degree of the weighing country and the comprehensive national force, the logistics operation not only determines the total operation cost of the business enterprises, but also directly influences the stability and the balance of the operation of the whole business system, and therefore the logistics transportation scheduling is one of the core activities of logistics.

In logistics transportation scheduling, one of the most basic logistics transportation scheduling models can be described as: a distribution center has a plurality of vehicles to be delivered to a plurality of customer sites, each vehicle departs from the distribution center, needs to go through all the customers for which the vehicle is responsible, and then returns to the distribution center, and how to select a traveling route is required to minimize the total travel. The vehicle capacity is larger than or equal to the total cargo demand of all the client points which are responsible for the vehicle; all customers can pass by one vehicle only once, but the existing logistics transportation scheduling method is slow in operation speed, weak in convergence capacity and low in optimization efficiency.

Disclosure of Invention

The invention provides a logistics transportation scheduling method and device based on a quantum firework algorithm, which are used for solving the technical problems of low running speed, weak convergence capacity and low optimization efficiency of the conventional logistics transportation scheduling method.

The invention provides a logistics transportation scheduling method based on a quantum firework algorithm, which comprises the following steps:

determining the number of customer points as n and the demand load W which is in one-to-one correspondence with the n customer points as { W }₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the explosion sparks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworks is R_upThe lower limit of the random key area of the fireworks is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

According to the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

Positioning fireworks x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, said sets C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

respectively aiming at x in each set by a maximum position method_ijSorting in descending order, the set C_imThe second dimension value of each element in the distribution vehicle m is the access sequence of the customer points of the distribution vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (1) a customer route of a delivery vehicle m, wherein the number of customer points borne by the delivery vehicle m is G_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle is obtained;

recording global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

Updating the number of exploding sparks S per firework_iExplosion radius A_i；

At each firework x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

randomly selecting GM fireworks in a firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

calculating the fitness value of newly generated explosion sparks and Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to a roulette plate rule, and selecting each alternative firework in the roulette plate rule according to the probability formula:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

If N is present_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimal fitness value fitness_best；

Updating a quantum mapped random number N_QmapMake N be_QmapIs [0, K ]]An internal random integer;

will Q fireworks x_iConversion to Q quanta Q_i；

For Q quantum Q_iCarrying out one-time quantum revolving door updating;

the N rotated quantum individuals q_iConverted into N firework units x_i', if x_i' than x_iPreferably, the fireworks x are updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

Outputting the best firework position x_bestFitness value of fit_best。

Preferably, said updating of the number of exploding sparks S per firework_iExplosion radius A_iThe method specifically comprises the following steps:

determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula specifically includes:

the fourth preset formula is specifically as follows:

preferably, the Q fireworks x_iConversion to Q quanta Q_iThe method specifically comprises the following steps:

to fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Is converted into quantum q by an eighth preset formula_i，The eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking a negative number.

Preferably, said pair of Q quantities Q_iThe updating of the quantum revolving gate for one time specifically comprises the following steps:

for Q quantum Q by a ninth preset formula_iAnd updating the quantum revolving door once, wherein the ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iQuantum state of j-th dimension position passing through quantum rotation gate, wherein rotation angle delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ijL may be determined by an eleventh preset formula, which is specifically:

wherein the angular direction s (α) is rotated_ij,β_ij) The method can be determined by an eleventh preset formula, and the eleventh preset formula specifically is as follows:

wherein,andand (4) determining the j-th dimension probability amplitude of the current optimal quantum of the algorithm.

Preferably, the N rotated quantum individuals q_iConverted into N firework units x_i' specifically, the method comprises the following steps:

subjecting the quantum to individual treatmentConverted into firework individual x through a twelfth preset formula_i', the twelfth preset formula specifically is:

the invention provides a logistics transportation scheduling device based on a quantum firework algorithm, which comprises:

a first determining module, configured to determine that the number of customer points is n, and the demand load W corresponding to the n customer points one-to-one is { W ═ W₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q, the number of the explosion sparks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworks is R_upThe lower limit of the random key area of the fireworks is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

a first generation module for randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

A first calculation module for calculating a first calculation value based on the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

A first grouping module for grouping the firework position x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, said sets C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

a first ordering module for respectively ordering x in each set by maximum position method_ijSorting in descending order, the set C_imThe second dimension value of each element in the distribution vehicle m is the access sequence of the customer points of the distribution vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (1) a customer route of a delivery vehicle m, wherein the number of customer points borne by the delivery vehicle m is G_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

the second calculation module is used for calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle is obtained;

recording global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

A first updating module for updating the number S of exploding sparks per firework_iExplosion radius A_i；

A first shifting module for shifting each of the fireworks x_iRandomly selecting z dimensions, carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate explosion sparks,the fifth preset formula is specifically as follows:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

the first variable module is used for randomly selecting GM fireworks in a firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

and the third calculation module is used for calculating the fitness value of the newly generated explosion sparks and the Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, and selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to the roulette wheel rule, wherein the probability formula of each alternative firework selected in the roulette wheel rule is as follows:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

a second updating module for updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

A third updating module for if N_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimum fitness value fitness_best；

A first conversion module for converting Q fireworks x_iConversion to Q quanta Q_i；

A fourth updating module for the Q quantity Q_iCarrying out one-time quantum revolving door updating;

a fifth updating module for updating the N rotated quantum individuals q_iConverted into N firework units x_i', if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

An output module for outputting the optimal firework positionPut x_bestFitness value of fit_best。

Preferably, said updating of the number of exploding sparks S per firework_iExplosion radius A_iThe method specifically comprises the following steps:

determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula specifically includes:

the fourth preset formula is specifically as follows:

preferably, the Q fireworks x_iConversion to Q quanta Q_iThe method specifically comprises the following steps:

to fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Is converted into quantum q by an eighth preset formula_i，The eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking a negative number.

Preferably, said pair of Q quantities Q_iThe updating of the quantum revolving gate for one time specifically comprises the following steps:

for Q quantum Q by a ninth preset formula_iAnd updating the quantum revolving door once, wherein the ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iQuantum state of j-th dimension position passing through quantum rotation gate, wherein rotation angle delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ijL may be determined by an eleventh preset formula, which is specifically:

wherein the angular direction s (α) is rotated_ij,β_ij) The method can be determined by an eleventh preset formula, and the eleventh preset formula specifically is as follows:

wherein,andand (4) determining the j-th dimension probability amplitude of the current optimal quantum of the algorithm.

Preferably, the N rotated quantum individuals q_iConverted into N firework units x_i' specifically, the method comprises the following steps:

subjecting the quantum to individual treatmentConverted into firework individual x through a twelfth preset formula_i', the twelfth preset formula specifically is:

according to the technical scheme, the invention has the following advantages:

according to the logistics transportation scheduling method based on the quantum firework algorithm, parameters such as the number of firework populations, explosion density and explosion radius in the firework algorithm are defined by analyzing an optimization mechanism of the firework algorithm and aiming at the described logistics transportation scheduling problem, a coding and decoding strategy combining an equally-divided random key and a vehicle path is designed, and a method for mutually converting quantum and fireworks is provided, so that the overall search capability of the algorithm is enhanced by introducing a quantum revolving door, and the technical problems of low operation speed, weak convergence capability and low optimization efficiency of the conventional logistics transportation scheduling method are solved.

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 description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic flow chart of an embodiment of a logistics transportation scheduling method based on a quantum firework algorithm provided by the invention;

fig. 2 is a schematic flow chart of another embodiment of a logistics transportation scheduling method based on a quantum firework algorithm provided by the invention;

fig. 3 is a schematic structural diagram of an embodiment of a logistics transportation scheduling device based on a quantum firework algorithm, provided by the invention;

FIG. 4 is an optimal path diagram of an application example of the logistics transportation scheduling method based on the quantum firework algorithm provided by the invention;

fig. 5 is a graph of the shortest path evolution of an application example of the logistics transportation scheduling method based on the quantum firework algorithm provided by the invention.

Detailed Description

The embodiment of the invention provides a logistics transportation scheduling method and device based on a quantum firework algorithm, and solves the technical problems of low running speed, weak convergence capacity and low optimization efficiency of the conventional logistics transportation scheduling method.

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, an embodiment of the present invention provides an embodiment of a logistics transportation scheduling method based on a quantum firework algorithm, including:

101, determining the number of customer points as n and the required load weight W corresponding to the n customer points one by one as { W }₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the explosion sparks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworks is R_upThe lower limit of the firework random key area is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

102, randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

103 according to the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

104 positioning the fireworks in x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, set C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

respectively aiming at x in each set by a maximum position method_ijSorting in descending order, set C_imThe second dimension value of each element is the access sequence of the client point of the delivery vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (3), a customer route of the delivery vehicle m, wherein the number G of customer points borne by the delivery vehicle m_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

106, calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the sum of the load demands of the customer points corresponding to the delivery vehicle exceeds the maximum load demand of the vehicleWeight difference of large load limit;

107 recording the global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current best firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

108, updating the number S of explosion sparks of each firework_iExplosion radius A_i；

109 in each firework x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

randomly selecting GM fireworks in the firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

calculating the fitness value of newly generated explosion sparks and Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to a roulette plate rule, and selecting each alternative firework in the roulette plate rule according to the probability formula:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

112, updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

113 if N_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimal fitness value fitness_best；

114 updating the quantum mapping random number N_QmapThe Q fireworks x_iConversion to Q quanta Q_iFor Q quantity Q_iPerforming one-time quantum revolving gate updating, and enabling the N quantum individuals q after the rotation_iConverted into N firework units x_i', if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

115 outputting the best fireworks position x_bestFitness value of fit_best。

According to the logistics transportation scheduling method based on the quantum firework algorithm, provided by the embodiment of the invention, parameters such as firework population number, explosion density and explosion radius in the firework algorithm are defined by analyzing an optimization mechanism of the firework algorithm and aiming at the described logistics transportation scheduling problem, an encoding and decoding strategy combining equally-divided random keys and vehicle paths is designed, and a method for mutually converting quantum and fireworks is provided, so that the overall search capability of the quantum revolving door enhanced algorithm is introduced, and the technical problems of low running speed, weak convergence capability and low optimization efficiency of the existing logistics transportation scheduling method are solved.

The above is a description of an embodiment of a logistics transportation scheduling method based on the quantum firework algorithm, and another embodiment of a logistics transportation scheduling method based on the quantum firework algorithm is described in detail below.

Referring to fig. 2, another embodiment of a method for drawing an order thermodynamic diagram distribution based on an electronic fence map according to the present invention includes:

201, determining the number of customer points as n, and the required load weight W corresponding to the n customer points one by one as { W }₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the explosion sparks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworksIs R_upThe lower limit of the firework random key area is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

202, randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

203 according to the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

204 firework position x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, set C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i<R_down+m·[(R_up-R_down)/K]}；

205 by maximum position method, respectively for x in each set_ijSorting in descending order, set C_imThe second dimension value of each element is the access sequence of the client point of the delivery vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (3), a customer route of the delivery vehicle m, wherein the number G of customer points borne by the delivery vehicle m_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

206, calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle;

207 recording the global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current best firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

208, determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula is specifically as follows:

the fourth preset formula is specifically as follows:

209 at each Firework x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

randomly selecting GM fireworks in a firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

calculating the fitness value of newly generated explosion sparks and Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to the roulette plate rule, and selecting each alternative firework in the roulette plate rule according to the probability formula:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

212 updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

213 if N_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimal fitness value fitness_best；

214 updating the quantum mapped random number N_QmapTo make fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Is converted into quantum q by an eighth preset formula_i，The eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking negative number, and applying a ninth preset formula to Q quantum Q_iCarrying out one-time quantum revolving door updating, wherein a ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iQuantum state of j-th dimension position passing through quantum rotation gate, wherein rotation angle delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ij| may be determined by an eleventh preset formula, which is specifically:

wherein, rotatedirection of rotation angle s (α)_ij,β_ij) The method can be determined by an eleventh preset formula, wherein the eleventh preset formula is specifically as follows:

wherein,andfor the j-dimension probability amplitude of the current optimal quantum of the algorithm, the quantum is subjected to individual analysisConverted into firework individual x through a twelfth preset formula_i', the twelfth preset formula specifically is:

if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

215 outputting the best Firework position x_bestFitness value of fit_best。

According to the logistics transportation scheduling method based on the quantum firework algorithm, provided by the embodiment of the invention, parameters such as firework population number, explosion density and explosion radius in the firework algorithm are defined by analyzing an optimization mechanism of the firework algorithm and aiming at the described logistics transportation scheduling problem, an encoding and decoding strategy combining equally-divided random keys and vehicle paths is designed, and a method for mutually converting quantum and fireworks is provided, so that the overall search capability of the quantum revolving door enhanced algorithm is introduced, and the technical problems of low running speed, weak convergence capability and low optimization efficiency of the existing logistics transportation scheduling method are solved.

The above is a description of an embodiment of a logistics transportation scheduling method based on the quantum firework algorithm, and a detailed description of an embodiment of a logistics transportation scheduling device based on the quantum firework algorithm is provided below.

Referring to fig. 3, an embodiment of a logistics transportation scheduling device based on a quantum firework algorithm provided by the invention includes:

a first determining module 301, configured to determine that the number of customer points is n, and the demand load W corresponding to the n customer points one to one is { W ═ W₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the exploding fireworks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworks is R_upThe lower limit of the random key area of the fireworks is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

a first generating module 302 for randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

A first calculating module 303 for calculating a position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

A first grouping module 304 for grouping the firework position x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, set C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

a first ordering module 305 for respectively ordering x in each set by a maximum position method_ijSorting in descending order, set C_imThe second dimension value of each element is the access sequence of the client point of the delivery vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (3), a customer route of the delivery vehicle m, wherein the number G of customer points borne by the delivery vehicle m_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

a second calculating module 306, configured to calculate a firework x according to a second preset formula according to the customer path of the delivery vehicle m in the solution of fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle;

recording global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

A first updating module 307 for updating the number of exploding sparks S per firework_iExplosion radius A_i；

A first migration module 308 for each firework x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

the first variation module 309 is configured to randomly select GM fireworks from the firework population, randomly select z dimensions for each firework to perform gaussian variation operation, and generate GM gaussian sparks for the randomly selected dimension k according to a seventh preset formula, where the seventh preset formula specifically is:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

a third calculating module 310, configured to calculate fitness values of the newly generated explosion sparks and the gaussian variation sparks, select an optimal individual from the original firework population, the explosion sparks and the gaussian variation sparks as a next generation firework population, and select the remaining (Q-1) next generation firework populations from the original firework population, the explosion sparks and the gaussian variation sparks according to the roulette wheel rule, where a probability formula selected by each candidate in the roulette wheel rule is:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

a second updating module 311 for updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen updating the optimal firework position x of the whole part_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

A third updating module 312 for if N_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd most preferablyBest fitness value fitness_best；

A first conversion module 313 for converting the Q fireworks x_iConversion to Q quanta Q_i；

A fourth updating module 314 for the Q quantities Q_iCarrying out one-time quantum revolving door updating;

a fifth updating module 315 for updating the N rotated quanta q_iConverted into N firework units x_i', if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimum fitness value fitness_best；

An output module 316 for outputting the optimal firework position x_bestFitness value of fit_best。

Optionally, the number of exploding sparks S per firework is updated_iExplosion radius A_iThe method specifically comprises the following steps:

determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula is specifically as follows:

the fourth preset formula is specifically as follows:

optionally, Q fireworks x_iConversion to Q quanta Q_iThe method specifically comprises the following steps:

to fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Converted into quanta qi by an eighth preset formula,the eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking a negative number.

Optionally, for Q quantity Q_iThe updating of the quantum revolving gate for one time specifically comprises the following steps:

for Q quantum Q by a ninth preset formula_iCarrying out one-time quantum revolving door updating, wherein a ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iDimension j position through quantumQuantum state after rotating the gate, wherein the angle of rotation is delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ij| may be determined by an eleventh preset formula, which is specifically:

wherein the angular direction s (is) of rotation_ij,β_ij) The method can be determined by an eleventh preset formula, wherein the eleventh preset formula is specifically as follows:

wherein,andand (4) determining the j-th dimension probability amplitude of the current optimal quantum of the algorithm.

Optionally, q is added to the N rotated quantum individuals_iConverted into N firework units x_i' specifically, the method comprises the following steps:

subjecting the quantum to individual treatmentConverted into the firework individual x by a twelfth preset formula_i', the twelfth preset formula specifically is:

one application example of the present invention is as follows.

First step, initialization:

(1) setting control parameters: maximum number of iterations N_maxIteration counter N (initial 0), population size of fireworks Q, number of explosion sparks S_sumThe explosion radius A of the fireworks, the Gaussian variation spark number GM and the upper limit R of the random key region of the fireworks_up4000 and lower limit R_down0, number of quantum-rotated iterations N_QmaxQuantum mapping random number N_QmapA constant ε of 10^-23。

(2) Initializing a population: for each i, randomly generating the ith firework with the position x_i。

Secondly, according to x of each firework in the initial firework population_iComputing a function adaptation value fitness_i。

In the case where the required load of 7 customer points is W { (230,300,400, 50,80,120,90}, the number of delivery vehicles is 4, and the maximum load limit of the 4 delivery vehicles is B { (500,500,700,200 }), it is assumed that the position of the ith firework is x_iFor the firework position x according to equation (1) {590,2600,1090,3600,1900,1200,3900}, the method is applied to the firework position x_iInternal real number x_ij(j 1,2, …,7) to generate 4 sets, set C_im(m ═ 1,2,3,4) is: c₁＝{(590,1)}， C₂＝{(1090,3)，(1900,5)，(1200,6)}，C₃＝{(2600,2)}，C₄＝{(3600,4)，(3900,7)}。

Then applying maximum position method to each set C_imInner x_ijThe descending order coding is carried out, and the following can be obtained: c₁＝{(590,1)}，C₂＝{(1900,5)，(1200,6)，(1090,3)}，C₃＝{(2600,2)}，C₄{ (3900,7), (3600,4) }. I.e. I can get a solution x_iThe vehicle path planning results are represented as follows: the path of the vehicle 1 is 0-1-0; the path of the vehicle 2 is 0-5-6-3-0; the path of the vehicle 3 is 0-2-0;the vehicle 4 path is 0-7-4-0, where 0 represents a delivery point.

According to the vehicle path planning result, the sum of the load demands of the customer points in charge of the vehicle 2 can be known to exceed the maximum load limit of the vehicle according to the formula (4), and finally the fitness can be obtained according to the formula (3)_iThe sum of 11 path lengths such as d (O,1), d (1, O), d (O,5), d (5,6), d (6,3), d (3, O), d (O,2), d (2, O), d (O,7), d (7,4) and d (4, O) and the excess load of the vehicle 2.

Thirdly, recording the global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework fitness is fitness_bNumber of iterations N with constant optimum value_Q＝0。

And step four, N is equal to N + 1.

Fifthly, updating the number S of the explosion sparks of each firework_iExplosion radius A_i。

Sixth step, each firework x_iGeneration of S_iAn explosion spark.

And seventhly, randomly selecting GM fireworks in the firework population (the same fireworks can be repeatedly selected), and randomly selecting z dimensions for each firework to perform Gaussian variation operation to generate GM Gaussian fireworks.

And eighthly, calculating the fitness values of the explosion sparks and the Gaussian sparks newly generated in the sixth step and the seventh step, and selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as the next-generation firework population. And (C) selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to the roulette plate rule.

Ninthly, updating the position x of the current optimal firework_bAnd fitness thereof_b. If fitness_bAnd fitness_bestSame, then N_Q＝N_Q+ 1; if fitness_bBetter than fitness_bestThen update the global maximumExcellent fireworks position x_best＝x_bAnd updating the fitness value fitness_best＝fitness_bRecording the worst firework adaptability value fitness_worst，N_Q＝0。

The tenth step, if N_Q≤N_QmaxTurning to the fourteenth step, otherwise, updating the quantum mapping random number N_Qmap。

The tenth step, Q fireworks x selected in the ninth step_iConversion to Q quanta Q_i。

(1) Quantum individual representation form: quantum individuals q_iState of each qubit ofIs expressed in the form of quantum angles, i.e.

(2) Suppose that the position of the ith firework is x_i＝{590,2600,1090,3600,1900,1200,3900}、N_Qmap＝2、 K＝4、R_up4000 and R_downThe firework x can be formed according to the formulas (11) and (12) when the firework x is 0_iConversion to quanta(three significant decimal places are reserved).

The twelfth step, suppose the pair quantaAnd carrying out one-time quantum revolving gate updating. Illustrated here for quantum q_iAnd quantum rotation updating is carried out on the quantum state of the middle 4-dimensional position. Wherein the fourth-dimensional state of the optimal quantum is set asfitness_i＝160，fitness_best＝120， fitness_worst＝235。

(1) determining the rotation direction of the rotation angle as s (α, beta) according to the formula (14)_ij＝-1。

(2) The magnitude of the angle of rotation is θ according to the formulas (15) and (16)_ij≈-0.278。

(3) Quantum spin gate update according to equation (17):

the tenth step is that the N rotated quantum individuals q are treated_iConverted into N firework units x_i'; if x_i' than x_iPreferably, the firework x is updated_i＝x_i'；

(1) Suppose after rotation the ith quantum state isN_Qmap＝2、K＝4、R_up4000 and R_down0, quantum q can be expressed according to equation (14)_iConverted into fireworks x_i'＝(2494 6123130 1606 3884 3176 1906)。

Fourteenth, updating the global optimal firework position x_bestAnd an optimal fitness value fitness_best。

Fifteenth step, if N is less than or equal to N_maxThen go to the fourth step.

Sixteenth step, outputting the best firework position x_bestFitness value of fit_best。

TABLE 1

The method provided by the invention is applied to solve the logistics transportation scheduling problem of 23 points (the problem comprises a distribution center, and the other 22 points are customer points), the solving process and the solving result are shown in table 1, fig. 4 and fig. 5, wherein table 1 is the parameter setting of the specific implementation of the method of the invention, fig. 4 is an optimal path diagram, and fig. 5 is a shortest path evolution curve diagram.

The logistics transportation scheduling method based on the quantum firework algorithm has the advantages of strong convergence capacity, strong global optimization capacity and high running speed, and shows good stability and effectiveness when solving logistics transportation scheduling. The specific implementation in this embodiment has been described in the above embodiments, and is not described here again.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the system and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed modules and methods may be implemented in other ways. For example, the above-described module embodiments are merely illustrative, and for example, a division of a module is merely a logical division, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

Modules described as separate parts may or may not be physically separate, and parts shown as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, each functional module in the embodiments of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.

The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the present invention as defined by the appended claims.

Claims (10)

1. A logistics transportation scheduling method based on a quantum firework algorithm is characterized by comprising the following steps:

determining the number of customer points as n and the demand load W which is in one-to-one correspondence with the n customer points as { W }₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the explosion sparks is S_sumThe explosive radius of the fireworks is A, the Gaussian variation fireThe upper limit of the area of the firework random key is R, the number of flowers is GM_upThe lower limit of the random key area of the fireworks is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

According to the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

Positioning fireworks x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, said sets C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

respectively aiming at x in each set by a maximum position method_ijSorting in descending order, the set C_imThe second dimension value of each element in the distribution vehicle m is the access sequence of the customer points of the distribution vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (1) a customer route of a delivery vehicle m, wherein the number of customer points borne by the delivery vehicle m is G_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle is obtained;

recording global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

Updating the number of exploding sparks S per firework_iExplosion radius A_i；

At each firework x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

randomly selecting GM fireworks in a firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

calculating the fitness value of newly generated explosion sparks and Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to a roulette plate rule, and selecting each alternative firework in the roulette plate rule according to the probability formula:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

If N is present_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimal fitness value fitness_best；

Updating a quantum mapped random number N_QmapMake N be_QmapIs [0, K ]]An internal random integer;

will Q fireworks x_iConversion to Q quanta Q_i；

For Q quantum Q_iCarrying out one-time quantum revolving door updating;

the N rotated quantum individuals q_iConverted into N firework units x_i', if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

Outputting the best firework position x_bestFitness value of fit_best。

2. The logistics transportation scheduling method based on quantum firework algorithm as claimed in claim 1, wherein the updating of the number of explosion sparks S of each firework_iExplosion radius A_iThe method specifically comprises the following steps:

determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula specifically includes:

the fourth preset formula is specifically as follows:

3. the logistics transportation scheduling method based on quantum firework algorithm as claimed in claim 2, wherein the Q fireworks x are processed_iConversion to Q quanta Q_iThe method specifically comprises the following steps:

to fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Is converted into quantum q by an eighth preset formula_i，The eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking a negative number.

4. The logistics transportation scheduling method based on quantum firework algorithm as claimed in claim 3, wherein the pair of Q quanta Q is provided_iThe updating of the quantum revolving gate for one time specifically comprises the following steps:

for Q quantum Q by a ninth preset formula_iAnd updating the quantum revolving door once, wherein the ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iQuantum state of j-th dimension position passing through quantum rotation gate, wherein rotation angle delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ijL may be determined by an eleventh preset formula, which is specifically:

wherein the angular direction s (α) is rotated_ij,β_ij) The method can be determined by an eleventh preset formula, and the eleventh preset formula specifically is as follows:

wherein,andand (4) determining the j-th dimension probability amplitude of the current optimal quantum of the algorithm.

5. Logistics transportation tone based on quantum firework algorithm as claimed in claim 4The method is characterized in that N rotated quantum individuals q are subjected to the rotation_iConverted into N firework units x_i' specifically, the method comprises the following steps:

subjecting the quantum to individual treatmentConverted into firework individual x through a twelfth preset formula_i', the twelfth preset formula specifically is:

6. the utility model provides a commodity circulation transportation scheduling device based on quantum fireworks algorithm which characterized in that includes:

a first determining module, configured to determine that the number of customer points is n, and the demand load W corresponding to the n customer points one-to-one is { W ═ W₁,w₂,…,w_nK delivery vehicles and B-B maximum load limit corresponding to the K delivery vehicles one by one₁,b₂,…,b_KThe maximum iteration times are N_maxThe group size of the fireworks is Q and the number of the explosion sparks is S_sumThe explosion radius of the fireworks is A, the number of Gaussian variation sparks is GM, and the upper limit of the random key area of the fireworks is R_upThe lower limit of the random key area of the fireworks is R_downQuantum rotation iteration number N_QmaxQuantum mapping random number N_QmapA constant epsilon;

a first generation module for randomly generating the ith firework with the position x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Wherein x is_ij∈[R_down,R_up)；

A first calculation module for calculating a first calculation value based on the position x of each firework in the initial firework population_iCalculating the corresponding function adaptation value fitness_i；

A first grouping module for grouping the firework position x_iEach real number x inside_ij(j ═ 1,2, …, n) grouping yields K sets, said sets C_im(m ═ 1,2, …, K) is:

C_im＝{(x_ij,j)|R_down+(m-1)·[(R_up-R_down)/K]≤x_i＜R_down+m·[(R_up-R_down)/K]}；

a first ordering module for respectively ordering x in each set by maximum position method_ijSorting in descending order, the set C_imThe second dimension value of each element in the distribution vehicle m is the access sequence of the customer points of the distribution vehicle mDetermining the ith firework x according to the access sequence_iIn the solution of (1) a customer route of a delivery vehicle m, wherein the number of customer points borne by the delivery vehicle m is G_mThe rule of a first preset formula is met, and the first preset formula specifically comprises:

the second calculation module is used for calculating the fireworks x through a second preset formula according to the customer path of the delivery vehicle m in the solution of the fireworks_iFunction adaptation value of (1)_iThe second preset formula is as follows:

wherein d (j)_mp,j_m(p+1)) Is a customer point j_mpAnd a customer point j_mpDistance between d (O, j)_m1) Is a customer point j_m1The distance from the point of initial delivery,for the customer to orderThe distance from the point of initial delivery,the weight difference that the sum of the load demands of the customer points corresponding to the distribution vehicle exceeds the maximum load limit of the vehicle is obtained;

recording global optimal firework position x_bestAnd its fitness value fitness_best＝fitness_bWherein the current optimal firework adaptability is fitness_bNumber of iterations N with constant optimum value_Q＝0；

A first updating module for updating the number S of exploding sparks per firework_iExplosion radius A_i；

A first shifting module for shifting each of the fireworks x_iRandomly selecting z dimensions, and carrying out position offset on the randomly selected dimension k belonging to {1,2, …, z } according to a fifth preset formula to generate an explosion spark, wherein the fifth preset formula specifically comprises the following steps:

wherein U (-1,1) is the interval [ -1,1 [ ]]When sparking, is uniformly distributedExceeding the boundary on the dimension k, performing border crossing detection through a mapping rule of a sixth preset formula, and mapping to a new position, wherein the sixth preset formula specifically comprises:

the first variation module is used for randomly selecting GM fireworks in a firework population, randomly selecting z dimensions for each firework to perform Gaussian variation operation, and generating GM Gaussian sparks for the randomly selected dimension k according to a seventh preset formula, wherein the seventh preset formula specifically comprises the following steps:

wherein e is a gaussian distribution with a mean of 1 and a variance of 1;

the third calculation module is used for calculating the fitness value of the newly generated explosion sparks and the Gaussian variation sparks, selecting the optimal individual from the original firework population, the explosion sparks and the Gaussian variation sparks as a next-generation firework population, selecting the rest (Q-1) next-generation firework populations from the original firework population, the explosion sparks and the Gaussian variation sparks according to the roulette plate rule, and selecting each alternative firework according to the roulette plate rule according to the probability formula that the alternative firework is selected in the roulette plate rule:

wherein, F_sumFor the total number of the original firework population, the explosion sparks and the Gaussian variation sparks in the iteration,as the distance between the individual in the candidate firework and the other candidate individuals,the distance sum of all the candidate firework individuals and other candidate individuals is obtained;

a second updating module for updating the position x of the current optimal firework_bAnd corresponding fitness_bIf fitness_bAnd fitness_bestSame, then N_Q＝N_Q+1, if fitness_bBetter than fitness_bestThen the global optimal firework position x is updated_best＝x_bAnd updating the fitness value fitness_best＝fitness_b，N_Q＝0；

A third updating module for if N_Q≤N_QmaxThen the global optimal firework position x is updated_bestAnd an optimal fitness value fitness_best；

A first conversion module for converting Q fireworks x_iConversion to Q quanta Q_i；

A fourth updating module for the Q quantity Q_iCarrying out one-time quantum revolving door updating;

a fifth updating module for updating the N rotated quantum individuals q_iConverted into N firework units x_i', if x_i' than x_iPreferably, the firework x is updated_i＝x_i', and update the global optimal firework position x_bestAnd an optimal fitness value fitness_best；

An output module for outputting the optimal firework position x_bestFitness value of fit_best。

7. The logistics transportation scheduling device based on quantum firework algorithm as claimed in claim 6, wherein the updating of the number of explosion sparks S per firework_iExplosion radius A_iThe method specifically comprises the following steps:

determining the fitness corresponding to the ith firework as x_i＝(x_i1,x_i2,…,x_in) The current optimal firework position is x_b＝(x_b1,x_b2,…,x_bn) The corresponding fitness is fitness_bThe current worst firework position is x_w＝(x_w1,x_w2,…,x_wn) The corresponding fitness is fitness_wUpdating the number S of the explosion sparks of each firework through a third preset formula and a fourth preset formula_iExplosion radius A_iThe third preset formula specifically includes:

the fourth preset formula is specifically as follows:

8. the method according to claim 7The logistics transportation scheduling device of the quantum firework algorithm is characterized in that Q fireworks x are used_iConversion to Q quanta Q_iThe method specifically comprises the following steps:

to fireworks x_i＝(x_i1,x_i2,…,x_ij,…,x_in) Is converted into quantum q by an eighth preset formula_i，The eighth preset formula specifically is:

if | cos θ_ij|≥|sinθ_ijI, then sin θ_ijTaking a positive number, otherwise sin θ_ijTaking a negative number.

9. The logistics transportation scheduling device based on quantum firework algorithm as claimed in claim 8, wherein the pair of Q quanta Q is provided_iThe updating of the quantum revolving gate for one time specifically comprises the following steps:

for Q quantum Q by a ninth preset formula_iAnd updating the quantum revolving door once, wherein the ninth preset formula specifically comprises:

wherein,is quantum q_iThe current quantum state of the j-th dimension location,is quantum q_iQuantum state of j-th dimension position passing through quantum rotation gate, wherein rotation angle delta theta_ijThe method can be determined by a tenth preset formula, and the tenth preset formula specifically is as follows:

Δθ_ij＝s(α_ij,β_ij)·|Δθ_ij|；

wherein the rotation angle is of magnitude | Δ θ_ijL may be determined by an eleventh preset formula, which is specifically:

wherein the angular direction s (α) is rotated_ij,β_ij) The method can be determined by an eleventh preset formula, and the eleventh preset formula specifically is as follows:

wherein,andand (4) determining the j-th dimension probability amplitude of the current optimal quantum of the algorithm.

10. The logistics transportation scheduling device based on quantum firework algorithm as claimed in claim 9, wherein the N number of rotated quantum individuals q are selected_iConverted into N firework units x_i' specifically, the method comprises the following steps:

subjecting the quantum to individual treatmentConverted into firework individual x through a twelfth preset formula_i', the twelfth preset formula specifically is: