CN113379205A - Machine set scheduling method - Google Patents

Machine set scheduling method Download PDF

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CN113379205A
CN113379205A CN202110589044.2A CN202110589044A CN113379205A CN 113379205 A CN113379205 A CN 113379205A CN 202110589044 A CN202110589044 A CN 202110589044A CN 113379205 A CN113379205 A CN 113379205A
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王金良
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Shanghai Chunqiu Aviation Technology Co ltd
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Abstract

The invention discloses a unit scheduling method, which comprises the following steps: deploying an algorithm, adding an algorithm module in a scheduling system, collecting data required by the algorithm and calculating an optimal solution, wherein the algorithm module comprises: the automatic ring assembling model comprises an automatic ring assembling model and a scheduling model, wherein the automatic ring assembling model comprises the following steps:
Figure DDA0003088737190000011
s.t.
Figure DDA0003088737190000012
xj∈Z+for j ═ 1, …, the n (2) shift model is as follows:
Figure DDA0003088737190000013
s.t.
Figure DDA0003088737190000014
Figure DDA0003088737190000015
xj∈Z+,for j＝1,…,nyinot less than 0, for i is 1, …, m. Compared with the prior art, the method and the device have the advantages that the problems of manual adjustment of a heuristic algorithm and dependence on experience are solved, and the special parameter requirements of domestic unit flights are improved while a set coverage and set segmentation model is adopted.

Description

Machine set scheduling method
Technical Field
The invention relates to the field of a scheduling algorithm of a unit, in particular to a scheduling method of the unit.
Background
The early machine set scheduling is mainly manually scheduled in a paper table or an electronic table, and the scheduling quality mainly depends on the experience of a first-line scheduling staff. Later, many airlines develop a unit scheduling system, the unit scheduling is also changed into system scheduling from original paper or spreadsheet scheduling, the system scheduling realizes automatic inspection of scheduling rules, human errors are avoided, but the scheduling effect still depends on the experience of a first-line scheduling worker at the moment, and no standard is provided for measuring the scheduling quality. Later, some unit scheduling systems develop an automatic scheduling function, but the automatic scheduling system is only semi-automatic, because the system depends on a scheduling template and needs manual adjustment, and the adopted algorithm is mainly a heuristic algorithm. The advantages of these methods are mainly high operation efficiency, but the quality of the solution is not very high and the robustness of the solution is also poor.
In order to solve the above problems, we have made a series of improvements.
Disclosure of Invention
The invention aims to provide a unit scheduling method to overcome the defects in the prior art.
A unit scheduling method comprises the following steps: the method comprises the following steps of deploying an algorithm, adding an algorithm module into a scheduling system, collecting data required by the algorithm and calculating an optimal solution, wherein the method sequentially comprises the following steps:
step (1), an algorithm is deployed on an algorithm server;
step (2), adding an algorithm module into the unit scheduling system, wherein the algorithm module comprises an automatic group ring model and a scheduling model, and the automatic group ring model comprises the following steps:
Figure BDA0003088737180000011
s.t.
Figure BDA0003088737180000012
xj∈Z+,for j＝1,…,n (2)
the shift model is as follows:
Figure BDA0003088737180000021
s.t.
Figure BDA0003088737180000022
Figure BDA0003088737180000023
xj∈Z+,for j＝1,…,n
yi≥0,for i＝1,…,m；
step (3), collecting data required by the algorithm and transmitting the data to an algorithm server, and transmitting the generated optimal solution to a system after the algorithm server operates;
wherein, in the automatic loop-group model, n is the number of legal calls generated, K is the number of flights to be scheduled, and CjCost of pairing j, akj1 if flight k can be assigned to pairing j otherwise 0, xjWhether pairing j is selected;
wherein, in the shift model, n is the number of generated shift lists, m is the number of pairing, T is the number of machine lengths, CjBalance index, B, of the Bank Table jij1 if pairing i is ranked to the shift schedule j otherwise 0, Ptj1 if the schdule table j is assigned to the captain t and 0, x otherwisej1, if the shift table j is selected, otherwise 0, yi1 if pairing i cannot be sorted into the shift list otherwise 0.
Further, the algorithm running step in the step (3) comprises: step A: step one generating Pairing and step B: generating registering;
wherein, step A includes: step a 1: generating a connection network between flights, step a 2: generating a one-day task Duty using a search algorithm, step a 3: utilizing a map method to connect Duty to produce legal Pairing, and the step a 4: is the cost of calculating the generated Pairing, step a 5: establishing an integer programming model by using an optimization engine, and finally generating a batch of Pairing with the minimum cost, so that each flight is covered at least once;
wherein, step B includes: step b 1: generating an initial feasible solution, step b 2: establishing a Pairing connection network, generating all feasible scheduling lists by adopting a searching method, and performing step b 3: calculating the balance index of the shift schedule of the step b2, and the step b 4: and (4) establishing an integer programming model by using an optimization engine, adding the initial feasible solution of the step b1 and the newly generated feasible scheduling table of the step b2 into the newly-established model, and finally generating a batch of scheduling tables with optimal balance, so that each Pairing is covered once.
Further, the cost setting of the step a4 includes: flight hour fee, overnight cost, set cost, short dispatch fee, traffic fee.
Further, the cost setting of the step b3 includes: the flight time is balanced, the fatigue degree is balanced, and the number of times of going overnight is balanced.
The invention has the beneficial effects that:
compared with the prior art, the method and the device have the advantages that the problems of manual adjustment of a heuristic algorithm and dependence on experience are solved, and the special parameter requirements of domestic unit flights are improved while a set coverage and set segmentation model is adopted.
Detailed Description
The present invention will be further described with reference to the following examples. It should be understood that the following examples are illustrative only and are not intended to limit the scope of the present invention.
Example 1
A unit scheduling method comprises the following steps: the method comprises the following steps of deploying an algorithm, adding an algorithm module into a scheduling system, collecting data required by the algorithm and calculating an optimal solution, wherein the method sequentially comprises the following steps:
step (1), an algorithm is deployed on an algorithm server;
step (2), adding an algorithm module into the unit scheduling system, wherein the algorithm module comprises an automatic group ring model and a scheduling model, and the automatic group ring model comprises the following steps:
Figure BDA0003088737180000031
s.t.
Figure BDA0003088737180000032
xj∈Z+,for j＝1,…,n (2)
the shift model is as follows:
Figure BDA0003088737180000033
s.t.
Figure BDA0003088737180000034
Figure BDA0003088737180000035
xj∈Z+,for j＝1,…,n
yi≥0,for i＝1,…,m；
step (3), collecting data required by the algorithm and transmitting the data to an algorithm server, and transmitting the generated optimal solution to a system after the algorithm server operates;
wherein, in the automatic loop-group model, n is the number of legal calls generated, K is the number of flights to be scheduled, and CjCost of pairing j, akj1 if flight k can be assigned to pairing j otherwise 0, xjWhether pairing j is selected;
wherein, in the shift model, n is the number of generated shift lists, m is the number of pairing, T is the number of machine lengths, CjBalance index, B, of the Bank Table jij1 if pairing i is ranked to the shift schedule j otherwise 0, Ptj1 if the schdule table j is assigned to the captain t and 0, x otherwisej1, if the shift table j is selected, otherwise 0, yi1 if pairing i cannot be sorted into the shift list otherwise 0.
The algorithm operation step in the step (3) comprises the following steps: step A: step one generating Pairing and step B: generating registering;
wherein, step A includes: step a 1: generating a connection network between flights, step a 2: generating a one-day task Duty using a search algorithm, step a 3: utilizing a map method to connect Duty to produce legal Pairing, and the step a 4: is the cost of calculating the generated Pairing, step a 5: establishing an integer programming model by using an optimization engine, and finally generating a batch of Pairing with the minimum cost, so that each flight is covered at least once;
wherein, step B includes: step b 1: generating an initial feasible solution, step b 2: establishing a Pairing connection network, generating all feasible scheduling lists by adopting a searching method, and performing step b 3: calculating the balance index of the shift schedule of the step b2, and the step b 4: and (4) establishing an integer programming model by using an optimization engine, adding the initial feasible solution of the step b1 and the newly generated feasible scheduling table of the step b2 into the newly-established model, and finally generating a batch of scheduling tables with optimal balance, so that each Pairing is covered once.
The cost setting of step a4 includes: flight hour fee, overnight cost, set cost, short dispatch fee, traffic fee.
The cost setting of step b3 includes: the flight time is balanced, the fatigue degree is balanced, and the number of times of going overnight is balanced.
The invention is designed based on the operational research cost minimization theory, and mainly adopts a set coverage and set segmentation model. The method is characterized in that an optimal solution can be solved, and the deviation degree of the output solution and the optimal solution can be controlled. The heuristic algorithm mainly differs from the current domestic unit scheduling: the heuristic algorithm is an algorithm constructed based on intuition or experience, and can give acceptable calculation cost for an example of an optimization problem, such as calculation time, occupied space and the like, and give an approximate optimal solution, and the deviation degree of the approximate solution from the real optimal solution can not be predicted in advance.
The basic principle of the invention is also the method principle adopted by the foreign mainstream machine set scheduling algorithm. But the effect of the foreign unit scheduling system used in China is not ideal at present. Mainly because foreign technologies do not take into account some of the domestic needs. For example: the domestic season-changing group ring is formed by firstly generating a group guide table, and is only locally adjusted on the basis of the group guide table at ordinary times, while foreign algorithm design is not designed on the basis of the group guide problem. FromThe calculation of the cost of the dynamic group ring is greatly different from foreign countries, and mainly comprises hour fee, overnight fee, traffic fee, and boarding fee. The automatic scheduling is not considered in foreign countries except for considering the flight time balance of the unit, the fatigue degree of the unit, the reasonability of people collocation and the like. Therefore, the optimization target and the optimization rule of the unit scheduling algorithm are greatly different from those of foreign countries. In terms of model: optimization objective CjThe content contained in the model is completely different from foreign countries, the rules in the model are different from the foreign countries, the unit collocation constraint, the unit fatigue limit and the like are increased, the Duty search algorithm adopts a segmented depth search method, and the search speed is improved compared with the foreign countries.
The specific use cases of the algorithm module of the present invention are exemplified: a description is given of how flight data of a flight schedule implements an automatic group ring. Wherein: the number inside the frequency, e.g., 12345, indicates that flight 110 has 1, 2, 3, 4, 5 weekly. Airport A, C, D belongs to the base of the airline.
Flight number Departure time Departure airport Time of arrival To an airport Frequency of
110 8:00 A 9:00 B 12345
120 12:30 C 14:00 D 123456
130 15:00 D 16:00 A 123457
121 10:00 B 11:00 C 1234567
112 17:00 A 18:20 B 1234567
122 15:00 C 16:30 A 1234567
123 11:00 B 12:15 C 12345
From these flights we can construct the following flight ring: the ring is defined as a closed loop which is started from a base and finally returns to the original base, and is formed by connecting flights, wherein the flight connection satisfies that an airport can be connected, and the time can also be connected. Can be returned on the same day or after a few days, and can be returned overnight outdoors in the middle of a few days. For example, P1 is a one-day ring formed by connecting four flights 110, 121, 120, 130, and the ring is from base a and finally back to a, and the connection between flights 110 and 121 satisfies: the departure airport of flight 121 is the same as the landing airport of flight 110, and the departure time of flight 121 is longer than the landing time of flight 110. Thus, flights 110, 121, 120, 130 may form a legal one-day ring. There is also a multi-day loop, such as P5, where the unit takes the flight from base a the first day, then overnight at airport B, and returns to base a the next day after taking flights 121, 120, 130. The cost is mainly composed of an hour fee and the like, for example, ring P1, and the cost to be paid by the flight crew 110, 121, 120, 130 is 350 yuan.
Flight ring Day one The next day The third day Cost of Base station
P1 110-121-120-130 Repetition of Repetition of 350 A
P2 110-123-120-130 Repetition of Repetition of 425 A
P3 110-121-122 Repetition of Repetition of 350 A
P4 110-123-122 Repetition of Repetition of 375 A
P5 112 121-120-130 Repeating the first day 583 A
P6 112 121-122 Repeating the first day 483 A
P7 120-130-112 121 Repeating the first day 583 C
P8 122-112 123 Repeating the first day 408 C
P9 120-130-112 123 Repeating the first day 608 C
P10 122-112 121 Repeating the first day 483 C
P11 130 110-123-120 Repeating the first day 575 D
P12 130 110-121-120 Repeating the first day 550 D
P13 130 112 121-120 633 D
Using the data for the flight ring generated above, the following mathematical model can be built: description of (c)iIs the cost of ring i, xiI.e. ring i, if the value is 1 after solving, it means that the ring is selected, and if it is 0, it means that the ring is discarded. Each row of constraints under the optimization objective corresponds to each flight, the first constraint corresponds to flight 110, the second constraint corresponds to flight 120, and so on. Each constraint is equal to 1, indicating that each flight must be covered once. E.g. a first constraint x1+x2+x3+x4+x11+x12The meaning of 1 is that since the rings P1, P2, P3, P4, P11 and P12 all contain the flight 110, to cover the flight 110, it is necessary to select among these ringsOne can be taken, others can be analogized.
Figure BDA0003088737180000071
s.t.x1+x2+x3+x4+x11+x12＝1
x1+x3+x5+x6+x7+x10+x12+x13＝1
x1+x2+x5+x7+x9+x11+x12+x13＝1
x3+x4+x6+x8+x10＝1
x1+x2+x5+x7+x9+x11+x12+x13＝1
x5+x6+x7+x8+x9+x10+x13＝1
x2+x4+x8+x9+x11＝1
xi＝0,1；i＝1,2,Λ,13
Using an optimization engine, such as GUROBI or ILOG, the optimal set of rings can be solved as: p1, P8.
While the present invention has been described with reference to the specific embodiments, the present invention is not limited thereto, and various changes may be made without departing from the spirit of the present invention.

Claims (4)

1. A unit scheduling method comprises the following steps: the method comprises the following steps of deploying an algorithm, adding an algorithm module into a scheduling system, collecting data required by the algorithm and calculating an optimal solution, and is characterized in that: the method sequentially comprises the following steps:
step (1), an algorithm is deployed on an algorithm server;
step (2), adding an algorithm module into the unit scheduling system, wherein the algorithm module comprises an automatic group ring model and a scheduling model, and the automatic group ring model comprises the following steps:
Figure FDA0003088737170000011
s.t.
Figure FDA0003088737170000012
xj∈Z+,for j＝1,…,n (2)
the shift model is as follows:
Figure FDA0003088737170000013
s.t.
Figure FDA0003088737170000014
Figure FDA0003088737170000015
xj∈Z+,for j＝1,…,n
yi≥0,for i＝1,…,m；
step (3), collecting data required by the algorithm and transmitting the data to an algorithm server, and transmitting the generated optimal solution to a system after the algorithm server operates;
wherein, in the automatic loop-group model, n is the number of legal calls generated, K is the number of flights to be scheduled, and CjCost of pairing j, akj1 if flight k can be assigned to pairing j otherwise 0, xjWhether pairing j is selected;
wherein, in the shift model, n is the number of generated shift lists, m is the number of pairing,
Number of machine lengths, CjThe balance index of the shift table j,
Bij1 if pairingi is ranked to the shift list j otherwise 0,
Ptj1 if the shift table j is assigned to the captain t otherwise 0,
xj1 if the shift table j is selected or 0,
yi1 if pairingi cannot be sorted into the shift table otherwise 0.
2. A unit scheduling method according to claim 1, characterized in that: the algorithm operation step in the step (3) comprises the following steps: step A: step one generating Pairing and step B: generating registering;
wherein, step A includes: step a 1: generating a connection network between flights, step a 2: generating a one-day task Duty using a search algorithm, step a 3: utilizing a map method to connect Duty to produce legal Pairing, and the step a 4: is the cost of calculating the generated Pairing, step a 5: establishing an integer programming model by using an optimization engine, and finally generating a batch of Pairing with the minimum cost, so that each flight is covered at least once;
wherein, step B includes: step b 1: generating an initial feasible solution, step b 2: establishing a Pairing connection network, generating all feasible scheduling lists by adopting a searching method, and performing step b 3: calculating the balance index of the shift schedule of the step b2, and the step b 4: and (4) establishing an integer programming model by using an optimization engine, adding the initial feasible solution of the step b1 and the newly generated feasible scheduling table of the step b2 into the newly-established model, and finally generating a batch of scheduling tables with optimal balance, so that each Pairing is covered once.
3. A unit scheduling method according to claim 2, characterized in that: the cost setting of the step a4 comprises the following steps: flight hour fee, overnight cost, set cost, short dispatch fee, traffic fee.
4. A unit scheduling method according to claim 2, characterized in that: the cost setting of the step b3 comprises the following steps: the flight time is balanced, the fatigue degree is balanced, and the number of times of going overnight is balanced.
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