CN114021895A - Method and system for scheduling IT operation and maintenance personnel with minimized total cost based on neighborhood structure - Google Patents

Method and system for scheduling IT operation and maintenance personnel with minimized total cost based on neighborhood structure Download PDF

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CN114021895A
CN114021895A CN202111175286.3A CN202111175286A CN114021895A CN 114021895 A CN114021895 A CN 114021895A CN 202111175286 A CN202111175286 A CN 202111175286A CN 114021895 A CN114021895 A CN 114021895A
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刘振元
陈芮莹
刘恒岭
展月
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Huazhong University of Science and Technology
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Abstract

The invention discloses a method and a system for scheduling IT operation and maintenance personnel with minimized total cost based on a neighborhood structure, and belongs to the field of personnel scheduling. The method comprises the following steps: under the constraints of fault processing task execution and the service skill level of operation and maintenance personnel, establishing an operation and maintenance personnel scheduling model taking the minimum total cost as a target; the method comprises the steps of obtaining the deadline, the importance degree, the emergency degree, the unit delay cost and the standard execution time of each task, obtaining the skill level and the unit time cost of each operation and maintenance worker, solving by adopting a variable neighborhood genetic algorithm to obtain an optimal worker and task combination scheme, representing individuals by adopting two chromosomes with the same length, wherein each gene position of one chromosome is a task number, and each gene position of the other chromosome is an operation and maintenance worker number for processing the corresponding task. The invention uses the genetic algorithm operator designed aiming at the minimum total cost and the neighborhood structure of the variable neighborhood algorithm, can still obtain better results in large-scale cases, and has high solving speed.

Description

Method and system for scheduling IT operation and maintenance personnel with minimized total cost based on neighborhood structure
Technical Field
The invention belongs to the field of personnel scheduling, and particularly relates to a method and a system for scheduling IT operation and maintenance personnel for minimizing total cost based on a neighborhood structure.
Background
With the continuous development of social economy in China, the depth and the breadth of the IT system construction are gradually enhanced, and the IT operation and maintenance service becomes a very concerned problem in various industries. How to make IT operation and maintenance service, ensure that IT assets run stably, safely and quickly, and process in time after a fault occurs, so that the problem that the influence of the fault is reduced to the greatest extent is a key concern of enterprises.
This type of problem is characterized by heterogeneity among the operation and maintenance personnel and different levels of importance, urgency and cut-off time for the tasks. Can be simply described as: various IT faults can occur within a certain time period, each fault is an operation and maintenance task, and the urgency degrees of the tasks are different. Tasks such as host damage, network problems, etc. are relatively high in level, and if not solved in time, a large cost is generated. In addition, the level of personnel reporting the fault is different. The higher the level of the personnel reporting the fault, the more urgent the fault proposed by the party needs to be processed, otherwise, the higher the cost is generated, which is called the importance level. The operation and maintenance tasks have different cut-off times, and if the tasks are completed after the cut-off times, delay cost is generated, wherein the delay cost is delay time multiplied by unit penalty cost multiplied by importance multiplied by emergency. At present, a batch of operation and maintenance personnel can be assigned to process various tasks, and the types of the tasks which can be processed by each operation and maintenance personnel and the time for processing each task are different. The unit work cost of each operation and maintenance personnel is different.
The main idea of the thesis "IT operation and maintenance human resource scheduling considering service level" is as follows: and obtaining an initial solution by adopting a basic greedy algorithm, and further calculating by using a standard genetic algorithm to obtain a better result. However, this method has the following disadvantages: 1. the importance degree of the task is only divided into three fixed levels; 2. and a standard genetic algorithm is adopted for calculation, so that the solving speed is low and the effect is poor. The main idea of the thesis "intelligent genetic algorithm for scheduling IT operation and maintenance personnel considering service level" is as follows: and calculating the scheduling problem of the IT operation and maintenance personnel by adopting an improved genetic algorithm with a self-adaptive operator. However, this method has the following disadvantages: 1. the importance degree of the task is still only divided into three fixed levels; 2. the group intelligent iteration process of the genetic algorithm consumes more calculation time, and the problem solving effect is limited in limited time. The main idea of the thesis "IT operation and maintenance personnel scheduling considering task release time" is as follows: and a characteristic variable neighborhood algorithm and a genetic algorithm are adopted to solve the problem of scheduling the IT operation and maintenance personnel with the release time. However, this method has the following disadvantages: the method is designed and generated aiming at the scheduling problem of IT operation and maintenance personnel with release time, the solving target is the minimum maximum delay time, the method is greatly different from the problem solving method, and the phenomena of long calculation time and poor effect can occur in the process of solving the problem.
Disclosure of Invention
Aiming at the defects and the improvement requirements of the prior art, the invention provides a method and a system for scheduling IT operation and maintenance personnel with the minimized total cost based on a neighborhood structure, and aims to provide a characteristic method which has good solution efficiency and short solution time for the scheduling problem of the IT operation and maintenance personnel with the minimized total cost, and the method can still obtain better performance and obtain an excellent scheduling scheme when facing the actual large-scale actual problems (the number of tasks is 170 and 320, and the number of the operation and maintenance personnel is 20-40).
To achieve the above object, according to a first aspect of the present invention, there is provided a method for scheduling minimum total cost IT operation and maintenance personnel based on a neighborhood structure, the method including:
establishing an IT operation and maintenance personnel scheduling model with the aim of minimizing the total cost under the IT fault processing task execution constraint and the IT operation and maintenance personnel service skill level constraint;
the method comprises the following steps of obtaining the deadline, the importance degree, the emergency degree, the unit delay cost and the standard execution time of each IT fault handling task, obtaining the skill level and the unit time cost of each IT operation and maintenance personnel, solving the scheduling model by adopting a variable neighborhood genetic algorithm, obtaining the optimal personnel and task combination scheme, wherein the optimal personnel and task combination scheme comprises a task set and a task sequence which are distributed, two chromosomes with the same length are adopted to represent a single individual, each gene position of one chromosome is a task number, each gene position of the other chromosome is an operation and maintenance personnel number for processing a corresponding task, and the variable neighborhood genetic algorithm adopts a variable neighborhood searching mode to generate a next generation population, and the method comprises the following steps:
(1) initializing neighborhood quantity VNS _ num and initial solution X, and enabling VNS _ num to be 4 and k to be 1;
(2) if k is greater than VNS _ num, outputting an optimal solution X, and ending, otherwise, turning to the step (3);
(3) generating a new solution X 'according to the neighborhood structure with the number of k, if the total cost corresponding to X' is less than the total cost corresponding to X, turning to the step (4), and if not, turning to the step (5);
(4) replacing the original solution with the new solution, wherein k is 1, and turning to the step (2);
(5) searching in the next neighborhood, namely k is k +1, and turning to the step (2);
the neighborhood structure with the number of 1 is two-point exchange, the neighborhood structure with the number of 2 is a sudden change generated by the cost of operation and maintenance personnel, the neighborhood structure with the number of 3 is a sudden change generated by the cost of task delay, and the neighborhood structure with the number of 4 is a reverse order.
Preferably, the neighborhood structure numbered 1 produces a new solution in the following way: and randomly generating two positions, judging whether the operation and maintenance personnel at the first position can complete the task at the second position, judging whether the operation and maintenance personnel at the second position can complete the task at the first position, and if so, exchanging the task at the first position with the task at the second position.
Has the advantages that: aiming at the phenomenon that the general variable neighborhood algorithm has weak solving capability on the mathematical problem induced by the method, the method expands the searching direction of the variable neighborhood algorithm in actual solving by changing the distribution result of two operation and maintenance tasks to personnel.
Preferably, the neighborhood structure numbered 2 generates a new solution in the following way: and finding the operation and maintenance personnel with the highest cost, randomly selecting one task from the task set processed by the operation and maintenance personnel, and redistributing the task to other operation and maintenance personnel.
Has the advantages that: aiming at the phenomenon that the general variable neighborhood algorithm has weak solving capability on the mathematical problem induced by the method, the method changes the distributed task scheduling result by selecting the operation and maintenance personnel with the largest cost, and directionally changes the searching direction of the neighborhood algorithm. The neighborhood is set as a second neighborhood of the variable neighborhood algorithm, so that the search direction of the variable neighborhood algorithm is restrained, and the algorithm solving speed is accelerated.
Preferably, the neighborhood structure numbered 3 produces a new solution in the following way: and finding the task with the largest delay cost, and redistributing the task to other operation and maintenance personnel.
Has the advantages that: aiming at the phenomenon that the general variable neighborhood algorithm has weak solving capability on the mathematical problem induced by the method, the method changes the distributed task scheduling result by selecting the task with the largest cost, and directionally changes the searching direction of the neighborhood algorithm. The neighborhood is set as a third neighborhood of the variable neighborhood algorithm, and the constraint effect on the search direction of the variable neighborhood algorithm is enhanced together with the second neighborhood, so that the algorithm solving speed is further accelerated.
Preferably, the neighborhood structure numbered 4 produces a new solution in the following way: randomly generating two gene positions for a chromosome representing a task sequence, reversing the gene sequence between the two gene positions, namely changing the task sequence, and keeping the corresponding relation between a task number and an operation and maintenance personnel number unchanged for another segment of chromosome.
Has the advantages that: aiming at the phenomenon that the solving capability of the general variable neighborhood algorithm on the mathematical problem induced by the invention is weak, the invention greatly influences the current scheduling scheme by changing the task sequence of a plurality of tasks in operation and maintenance personnel executing the tasks respectively, and prompts the variable neighborhood algorithm to jump out of local optimum. And setting the neighborhood as a fourth neighborhood of a variable neighborhood algorithm, and expanding the solving direction of the algorithm by generating large change on the scheduling result through the neighborhood when the first three neighborhoods are in local optimization.
Preferably, the IT operation and maintenance personnel scheduling model is as follows:
Figure BDA0003295228790000041
wherein Z represents the total cost, S represents the total number of operation and maintenance personnel, SalsThe unit time cost of the operation and maintenance personnel s is shown, M represents the total number of the operation and maintenance tasks, xsmIndicates whether the operation and maintenance personnel s process the task m, psmRepresenting the time required by the operation and maintenance personnel s to process the task m, which is the product of the skill level of the personnel and the standard execution time of the task, cmRepresenting the unit delay cost, pi, of task mmIndicating the urgency of task m, bmRepresenting the importance of task m, FmIndicating the actual completion time of task m, DmRepresents the deadline of task m, ()+Indicating that the ratio of the size to 0 is larger.
Has the advantages that: the problem that in the real IT operation and maintenance scheduling, confusion is understood and decision is difficult is solved. According to the invention, the task and the personnel are subjected to quantitative processing by analyzing the corresponding attributes and the association relation of the task and the IT operation and maintenance personnel, a mathematical model for minimizing the total cost is established, and a scheduling scheme applicable to the actual IT operation and maintenance scheduling is obtained by solving the mathematical model by means of an intelligent algorithm.
Preferably, the initial solution X is obtained by:
step 1: calculating the product of the emergency degree and the importance degree of each task, and arranging the tasks in a descending order according to the task product;
step 2: obtaining an operation and maintenance personnel set capable of processing the current task, calculating the cost generated by each operation and maintenance personnel in the set for processing the task, wherein the cost comprises labor cost, task processing cost and task delay cost, and distributing the task to the operation and maintenance personnel with the minimum total cost for processing the task;
step 3: step2 is cycled through until all tasks are scheduled.
Has the advantages that: aiming at the problem that the initial solution is poor and influences the solving effect of the variable neighborhood algorithm, the problem is that tasks are sequentially distributed to the personnel executing the corresponding tasks to the minimum through a greedy thought based on rules to obtain a better initial solution, and when the variable neighborhood algorithm designed aiming at the minimum total cost is used for solving on the initial solution, a solution with a better effect can be obtained in a fixed time period.
To achieve the above object, according to a second aspect of the present invention, there is provided a neighborhood structure-based minimum total cost IT operation and maintenance personnel scheduling system, comprising: a computer-readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is configured to read executable instructions stored in the computer-readable storage medium, and execute the method for scheduling the IT operation and maintenance staff for minimizing the total cost based on the neighborhood based structure according to the first aspect.
Generally, by the above technical solution conceived by the present invention, the following beneficial effects can be obtained:
aiming at the problem that faults in the IT field are not processed timely due to disorder in fault processing in the reality, so that more cost is spent in the fault processing process and important and serious faults still cannot be processed timely, the invention establishes a mathematical model to summarize the overall flow by quantitative analysis of fault tasks and characteristics of processing staff, and constructs an IT staff scheduling method for minimizing the total cost by taking the total cost as a target. Due to the fact that the genetic algorithm operator and the variable neighborhood algorithm neighborhood structure which are designed aiming at the minimum total cost are used, the method can still obtain a good result in a large-scale case, the solving speed is high, and the large-scale problem which cannot be solved by a solver can be solved.
Drawings
FIG. 1 is a flowchart of a method for scheduling IT operation and maintenance personnel for minimizing the total cost based on a neighborhood structure, provided by the invention;
FIG. 2 is a schematic representation of an individual provided by the present invention;
FIG. 3 is a schematic diagram of a crossover operator provided by the present invention;
FIG. 4 is a schematic diagram of a mutation operator provided by the present invention;
FIG. 5 is a flow chart of a variable neighborhood algorithm provided by the present invention;
fig. 6 is a schematic diagram of a neighborhood structure provided by the present invention, in which (a) is a schematic diagram of a neighborhood 1, (b) is a schematic diagram of a neighborhood 2, (c) is a schematic diagram of a neighborhood 3, and (d) is a schematic diagram of a neighborhood 4.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in FIG. 1, the invention provides a method for scheduling IT operation and maintenance personnel with minimized total cost based on a neighborhood structure, which comprises the following steps:
step 1: and acquiring the emergency degree, the importance degree and the deadline of each task and the processing time of each IT operation and maintenance personnel for processing each task, and establishing an IT operation and maintenance personnel scheduling model with the aim of minimizing the total cost.
And acquiring the emergency degree, the importance degree and the deadline of each task and the processing time of each task processed by each IT operation and maintenance personnel, wherein if a certain employee cannot complete a certain task, the completion time is set to be an infinite value, and the infinite value is larger than the maximum processing time of the task which is normally processed.
The IT operation and maintenance personnel scheduling model comprises the following steps:
Figure BDA0003295228790000071
wherein Z represents the total cost, S represents the total number of operation and maintenance personnel, SalsThe unit time cost of the operation and maintenance personnel s is shown, M represents the total number of the operation and maintenance tasks, xsmIndicates whether the operation and maintenance personnel s process the task m, psmRepresenting the time required by the operation and maintenance personnel s to process the task m, which is the product of the skill level of the personnel and the standard execution time of the task, cmRepresenting the unit delay cost, pi, of task mmIndicating the urgency of task m, bmRepresenting the importance of task m, FmIndicates that task m is actually finishedTime of arrival, DmRepresents the deadline of task m, ()+Indicating that the ratio of the size to 0 is larger.
The problem needs to satisfy the following constraints:
(1) and (4) task constraint: all tasks must be assigned and only completed by one operation and maintenance person. Expressions (2) and (3) represent the time when the task m actually starts processing and the time when the task m actually completes processing; equation (4) indicates that the task cannot be stopped once processing is started; the formula (5) shows that each task can be processed by only one operation and maintenance person at most at each moment; equation (6) indicates that all tasks must be processed within a time period; equation (7) indicates that each task is assigned to only one operation and maintenance person.
(2) And (4) operation and maintenance personnel constraint: the operation and maintenance personnel can only process one task at the same time. Equation (8) represents the task assigned to each operation and maintenance person; formula (9) indicates that each operation and maintenance person can only process one task at each moment; the formula (10) ensures the time availability of the operation and maintenance personnel.
Figure BDA0003295228790000072
Figure BDA0003295228790000073
Figure BDA0003295228790000074
Figure BDA0003295228790000081
Figure BDA0003295228790000082
Figure BDA0003295228790000083
Figure BDA0003295228790000084
Figure BDA0003295228790000085
Figure BDA0003295228790000086
Wherein the variables involved are shown in tables 1-3.
Table 1 set definitions
Figure BDA0003295228790000087
TABLE 2 Definitions of the parameters
Figure BDA0003295228790000088
Figure BDA0003295228790000091
TABLE 3 decision variables
Figure BDA0003295228790000092
Step 2: the number of individuals conforming to the size of the population scale is generated in this step as the contemporary population.
Two chromosomes of the same length are used to represent an individual. Each gene position of the first segment of chromosome represents the number of the task and represents the sequence information of task processing; each gene position of the second segment of chromosome represents the number of the operation and maintenance personnel handling the corresponding task, and represents the corresponding information between the task and the operation and maintenance personnel.
And step 3: sequentially selecting two individuals in the current generation population, randomly generating a random probability, if the probability is less than 0.9, performing cross operation to obtain two new individuals, and putting the two new individuals into the cross population, otherwise, not performing operation.
The crossover operation uses a two-point crossover: and performing two-point intersection on a first chromosome representing the task sequence, wherein a second chromosome is formed by ensuring that the corresponding relation between the operation and maintenance personnel and the tasks is unchanged. Specifically, the offspring 1 inherits the first segment of chromosome segment of the parent, sequentially selects a certain number of genes which are not inherited from the female parent chromosome according to a relative sequence as the second segment of chromosome segment of the offspring 1, and sequentially selects the genes which are not inherited from the parent chromosome according to the relative sequence as the third segment of chromosome segment of the offspring 1. The operation and maintenance personnel chromosomes of the offspring 1 and the corresponding relations between the operation and maintenance personnel in the parent and the tasks are kept consistent. Child 2 is exactly the opposite of child 1. And finally, obtaining the cross population.
And 4, step 4: generating a random probability for each individual in the current generation population, if the probability is less than 0.1, performing mutation operation to obtain a new individual, and putting the new individual into the mutation population, otherwise, not performing operation.
And the operation and maintenance personnel corresponding to the task are subjected to variation operation. The specific method comprises the following steps: randomly generating a gene locus and changing the operation and maintenance personnel corresponding to the gene locus task.
And 5: and calculating the fitness of all operators in the current generation population, the variation population and the cross population. And selecting individuals according with the size of the population from the current population, the variant population and the cross population by adopting a roulette selection method and an elite reservation strategy to update the current population.
Fitness function set as
Figure BDA0003295228790000101
The value range of the fitness function is [0,1 ]]Max is the maximum cost of the population, min is the minimum cost of the population, f (x)i) The cost incurred for the current chromosome.
The specific operation of roulette selection is as follows:
calculate the ith individual xiProbability of being inherited into next generation population
Figure BDA0003295228790000102
N is the population scale; calculating cumulative probability of each individual
Figure BDA0003295228790000103
In [0,1 ]]Generating a uniformly distributed pseudo-random number r in the interval; selecting an individual xkSo that: q (x)k-1)<r≤Q(xk) This is true.
Since roulette chooses based on the fitness of the individual, which may result in the optimal individual not being selected, the present invention employs an elite reservation strategy. The elite individual is the optimal individual in each generation, and the elite retention strategy ensures that the elite individual in each generation can be retained in the next generation without change.
Step 6: and (3) performing variable neighborhood search on the n individuals with the highest fitness in the contemporary population to replace the worst n individuals in the population, wherein n is an artificially set numerical value, generally takes a value between one tenth and three tenth of the population quantity, and can be adjusted according to experimental effects. And (7) obtaining a new generation of population after the variable neighborhood search is completed, and taking the new generation of population as the current generation of population to perform step 7.
The specific steps of the variable neighborhood search are as follows:
(1) initializing a neighborhood number VNS _ num to be 4 and an initial solution X, and enabling k to be 1;
(2) if k is greater than VNS _ num, outputting an optimal solution X, and ending the algorithm, otherwise, turning to (3);
(3) generating a new solution X 'according to the neighborhood structure k, if X' is better than X, turning to (4), otherwise, turning to (5);
(4) replacing the original solution with the new solution, and searching again from the first neighborhood, namely k is 1 and then turning to (2);
(5) and searching the next neighborhood, namely k is k +1, and the next neighborhood is rotated to (2).
The invention designs four neighborhood structures for variable neighborhood searching.
Neighborhood 1 is a two-point swap. The concrete mode is as follows: firstly, two positions are randomly generated, whether the operation and maintenance personnel at the first position can complete the task at the second position or not and whether the operation and maintenance personnel at the second position can complete the task at the first position or not are judged, and if yes, the task at the first position and the task at the second position are exchanged.
Neighborhood 2 is a sudden change caused by the cost of the operation and maintenance personnel. The concrete mode is as follows: and finding the operation and maintenance personnel with the highest cost, randomly selecting one task from the task set processed by the operation and maintenance personnel, and redistributing the task to other operation and maintenance personnel.
Neighborhood 3 is the abrupt change caused by the task delay cost. The concrete mode is as follows: and finding the task with the largest delay cost, and redistributing the task to other operation and maintenance personnel.
Neighborhood 4 is in reverse order. The concrete mode is as follows: two gene positions are randomly generated for the first segment of the chromosome, and the gene order between the two gene positions is reversed, i.e. the task order is changed. For the second segment of chromosome, the corresponding relation between the task number and the operation and maintenance personnel number is not changed.
If the total cost corresponding to X 'is less than the total cost corresponding to X, then solving for X' is superior to X.
And 7: and (4) judging whether the iteration times reach the termination times, if so, ending, and otherwise, entering the step (3).
Examples
The population scale of the genetic algorithm based on the variable neighborhood is M, and the iteration number is N. In this embodiment, M is 50, and N is 200.
Step 1: and acquiring the urgency degree, the importance degree and the deadline of each task and the processing time of each IT operation and maintenance personnel for processing each task.
A case of 3 employees, 8 tasks was obtained. After data preprocessing, the deadline of the task is DlWith {10,6,10,9,7,8,5,6}, the urgency of the task is DlWith {3,1,2,2,1,1,3,3}, the importance of the task is Dl30,10,10, 30,30 }. The time that the employee completes each task is represented as a matrix
Figure BDA0003295228790000121
If the completion time of a certain task is 999, it means that the employee cannot complete the task.
Step 2: in this step, the number of individuals of a size corresponding to the size of the population is generated as the contemporary population P1。
Here 50 individuals were generated. FIG. 2 shows one of the individuals, where the operation and maintenance staff 1 needs to process 3 tasks, task 1, task 5 and task 7; the operation and maintenance personnel 2 need to process 3 tasks, namely a task 4, a task 2 and a task 8; the operation and maintenance personnel 3 need to process 2 tasks, task 6 and task 3 respectively.
And step 3: and sequentially selecting two individuals in the current generation population to generate a random probability, if the probability is less than 0.9, performing cross operation to obtain two new individuals and putting the two new individuals into the cross population, otherwise, not performing operation.
In this example, the 1 st individual was taken out as the female parent and the 2 nd individual was taken out as the male parent, and the random probability was obtained to be 0.5 and less than 0.9, and the crossover operation was performed. As shown in fig. 3, the child 1 firstly inherits the first two tasks 3 and 7 from the father, then inherits the four tasks 4, 8, 2 and 5 which the child does not own from the mother, and finally inherits all the tasks 1 and 6 which the child does not own from the father, and the second operation and maintenance person chromosome keeps consistent with the corresponding relation of the operation and maintenance persons of the tasks in the father; the filial generation 2 firstly inherits the first two tasks 4 and 7 from the female parent, then inherits the four tasks 3, 2,1 and 5 which are not owned by the filial generation 2 from the male parent in sequence, and finally inherits all the tasks 8 and 6 which are not owned by the female parent, and the second operation and maintenance personnel chromosome keeps consistent with the corresponding relation of the task operation and maintenance personnel in the female parent. Step3 is carried out on the remaining 48 individuals to obtain a cross population P2。
And 4, step 4: generating a random probability for each individual in the current generation population, if the probability is less than 0.1, performing mutation operation to obtain a new individual, and putting the new individual into the mutation population, otherwise, not performing operation.
In this embodiment, mutation operation is first performed on the 1 st individual, and the generated random probability is 0.05, thenMutation operation is performed, and as shown in fig. 4, the randomly generated gene locus is task 7, and task 7 is reassigned to the operation and maintenance staff 1. Step 4 is carried out on the remaining 49 individuals to obtain a variation population P3。
And 5: calculating the fitness of all operators in the current generation population, the mutation population and the cross population, and adopting a roulette selection method and an elite retention strategy to carry out the fitness calculation in the current generation population P1Variant population P2And cross population P3To select 50 individuals to replace P1。
Step 6: at P1Selecting 5 individuals with highest fitness to carry out variable neighborhood search replacement P1The worst 5 individuals.
As shown in fig. 5, the specific steps of the variable neighborhood search are as follows:
(1) initializing a neighborhood number VNS _ num to be 4 and an initial solution X, and enabling k to be 1;
(2) if k is greater than VNS _ num, outputting an optimal solution X, and ending the algorithm, otherwise, turning to (3);
(3) generating a new solution X 'according to the neighborhood structure k, if X' is better than X, turning to (4), otherwise, turning to (5);
(4) replacing the original solution with the new solution, and searching again from the first neighborhood, namely k is 1 and then turning to (2);
(5) and searching the next neighborhood, namely k is k +1, and the next neighborhood is rotated to (2).
Neighborhood 1 is shown as (a) in fig. 6, if the operation and maintenance personnel 2 can process the task 4 and the operation and maintenance personnel 3 can process the task 7, then the exchange is performed, the operation and maintenance personnel 2 process the task 4 and the operation and maintenance personnel 3 process the task 7, and the relative sequence of the tasks in the task sequence of each operation and maintenance personnel is kept unchanged.
The neighborhood 2 is shown in fig. 6 (b), the operation and maintenance person with the largest cost is number 2, and the random selection task 7 is reassigned to the operation and maintenance person 3.
Neighborhood 3 is shown as (c) in fig. 6, the task with the largest delay cost is 7, and task 7 is reassigned to operation and maintenance person 1.
The neighborhood 4 is shown in (d) in fig. 6, and selects the first position and the second position, reverses the task between the two positions, and ensures that the correspondence between the operation and maintenance personnel and the task is unchanged. And 7, after the variable neighborhood search is completed, performing step 7.
And 7: and (4) judging whether the iteration times reach the termination times N, if so, ending, otherwise, entering the step 3.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (8)

1. A method for scheduling IT operation and maintenance personnel for minimizing total cost based on a neighborhood structure is characterized by comprising the following steps:
establishing an IT operation and maintenance personnel scheduling model with the aim of minimizing the total cost under the IT fault processing task execution constraint and the IT operation and maintenance personnel service skill level constraint;
the method comprises the following steps of obtaining the deadline, the importance degree, the emergency degree, the unit delay cost and the standard execution time of each IT fault handling task, obtaining the skill level and the unit time cost of each IT operation and maintenance personnel, solving the scheduling model by adopting a variable neighborhood genetic algorithm, obtaining the optimal personnel and task combination scheme, wherein the optimal personnel and task combination scheme comprises a task set and a task sequence which are distributed, two chromosomes with the same length are adopted to represent a single individual, each gene position of one chromosome is a task number, each gene position of the other chromosome is an operation and maintenance personnel number for processing a corresponding task, and the variable neighborhood genetic algorithm adopts a variable neighborhood searching mode to generate a next generation population, and the method comprises the following steps:
(1) initializing neighborhood quantity VNS _ num and initial solution X, and enabling VNS _ num to be 4 and k to be 1;
(2) if k is greater than VNS _ num, outputting an optimal solution X, and ending, otherwise, turning to the step (3);
(3) generating a new solution X 'according to the neighborhood structure with the number of k, if the total cost corresponding to X' is less than the total cost corresponding to X, turning to the step (4), and if not, turning to the step (5);
(4) replacing the original solution with the new solution, wherein k is 1, and turning to the step (2);
(5) searching in the next neighborhood, namely k is k +1, and turning to the step (2);
the neighborhood structure with the number of 1 is two-point exchange, the neighborhood structure with the number of 2 is a sudden change generated by the cost of operation and maintenance personnel, the neighborhood structure with the number of 3 is a sudden change generated by the cost of task delay, and the neighborhood structure with the number of 4 is a reverse order.
2. The method of claim 1, wherein the neighborhood structure numbered 1 is generated as a new solution as follows: and randomly generating two positions, judging whether the operation and maintenance personnel at the first position can complete the task at the second position, judging whether the operation and maintenance personnel at the second position can complete the task at the first position, and if so, exchanging the task at the first position with the task at the second position.
3. The method of claim 1, wherein the neighborhood structure numbered 2 generates a new solution as follows: and finding the operation and maintenance personnel with the highest cost, randomly selecting one task from the task set processed by the operation and maintenance personnel, and redistributing the task to other operation and maintenance personnel.
4. The method of claim 1, wherein the neighborhood structure numbered 3 generates a new solution as follows: and finding the task with the largest delay cost, and redistributing the task to other operation and maintenance personnel.
5. The method of claim 1, wherein the neighborhood structure numbered 4 generates a new solution as follows: randomly generating two gene positions for a chromosome representing a task sequence, reversing the gene sequence between the two gene positions, namely changing the task sequence, and keeping the corresponding relation between a task number and an operation and maintenance personnel number unchanged for another segment of chromosome.
6. The method of any of claims 1 to 5, wherein the IT operation and maintenance personnel scheduling model is as follows:
Figure FDA0003295228780000021
wherein Z represents the total cost, S represents the total number of operation and maintenance personnel, SalsThe unit time cost of the operation and maintenance personnel s is shown, M represents the total number of the operation and maintenance tasks, xsmIndicates whether the operation and maintenance personnel s process the task m, psmRepresenting the time required by the operation and maintenance personnel s to process the task m, which is the product of the skill level of the personnel and the standard execution time of the task, cmRepresenting the unit delay cost, pi, of task mmIndicating the urgency of task m, bmRepresenting the importance of task m, FmIndicating the actual completion time of task m, DmRepresents the deadline of task m, ()+Indicating that the ratio of the size to 0 is larger.
7. The method of claim 1 or 2, wherein the initial solution X is obtained by:
step 1: calculating the product of the emergency degree and the importance degree of each task, and arranging the tasks in a descending order according to the task product;
step 2: obtaining an operation and maintenance personnel set capable of processing the current task, calculating the cost generated by each operation and maintenance personnel in the set for processing the task, wherein the cost comprises labor cost, task processing cost and task delay cost, and distributing the task to the operation and maintenance personnel with the minimum total cost for processing the task;
step 3: step2 is cycled through until all tasks are scheduled.
8. A system for minimizing the total cost (IT) operation and maintenance personnel scheduling based on a neighborhood structure is characterized by comprising: a computer-readable storage medium and a processor;
the computer-readable storage medium is used for storing executable instructions;
the processor is used for reading executable instructions stored in the computer readable storage medium and executing the neighborhood structure-based minimum total cost IT operation and maintenance personnel scheduling method of any one of claims 1 to 7.
CN202111175286.3A 2021-10-09 2021-10-09 Method and system for scheduling IT operation and maintenance personnel with minimized total cost based on neighborhood structure Pending CN114021895A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116128258A (en) * 2023-04-17 2023-05-16 通号（长沙）轨道交通控制技术有限公司 Railway contact net maintainer configuration method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116128258A (en) * 2023-04-17 2023-05-16 通号（长沙）轨道交通控制技术有限公司 Railway contact net maintainer configuration method
CN116128258B (en) * 2023-04-17 2023-07-14 通号（长沙）轨道交通控制技术有限公司 Railway contact net maintainer configuration method

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