CN111667097A - Multi-chain search-based scheduling method for drivers of vehicles in same dispatching room - Google Patents

Multi-chain search-based scheduling method for drivers of vehicles in same dispatching room Download PDF

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CN111667097A
CN111667097A CN202010403816.4A CN202010403816A CN111667097A CN 111667097 A CN111667097 A CN 111667097A CN 202010403816 A CN202010403816 A CN 202010403816A CN 111667097 A CN111667097 A CN 111667097A
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郭建国
郭圆圆
阎磊
渠华
普秀霞
孙浩
赵新潮
白珂
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Zhengzhou Tiamaes Technology Co ltd
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Abstract

The invention discloses a scheduling method for drivers of vehicles in the same dispatching room based on multi-chain search, which comprises the steps of firstly searching a feasible scheduling solution of the vehicles based on a greedy tabu search algorithm; iteratively updating according to the limiting factors of the public transport enterprise to find a vehicle scheduling feasible solution which meets the requirements better; searching an optimal feasible solution according to the minimum loss cost to finally generate a feasible vehicle shift scheduling scheme; the bus enterprise appoints the maximum daily mileage of a driver to generate an initial solution for the driver to shift; generating a driver shift candidate set which meets the constraint condition by adopting chain search for a vehicle shift feasible scheme; and generating a final feasible scheme for the driver to shift according to the minimized driver cost. The invention considers the continuity of the same line in the design process and avoids the cross of different lines as much as possible. This improves the performability between shifts.

Description

Multi-chain search-based scheduling method for drivers of vehicles in same dispatching room
Technical Field
The invention belongs to the field of bus scheduling, and particularly relates to a driver scheduling technology of vehicles in a same dispatching room based on multi-chain search.
Background
The bus scheduling problem is essentially a combination optimization problem, but with the increasing scale of the problem, the time complexity and the calculation amount for obtaining the optimal solution will be exponentially increased, and finally become an NP-hard problem, so that the problem is generally accepted to be solved by adopting an intelligent technology in recent years in an academic sense. Intelligent algorithms have received widespread attention from the academic world since the beginning as an important branch of science and technology.
The technical scheme of scheduling vehicle drivers in the same dispatching room (Regional bus scheduling based Muti-chain technology) based on multi-chain search is a scheduling technique for balancing the relationship between vehicles and drivers on the premise of saving resources to a certain extent. The technology can well balance the labor time of a driver and also can give consideration to the resources of public transport enterprises. Compared with a single line, the scheduling mode can save resources as much as possible, and compared with the conventional regional scheduling technology, the scheduling mode can balance the labor time of a driver as much as possible, so that the labor efficiency of the driver is maximized on the premise of saving the resources of a bus enterprise as much as possible.
The driver scheduling technology of the same dispatching room vehicle based on multi-chain search is a typical NP-hard problem, and at present, the problems are solved mainly by adopting algorithms such as heuristic method, genetic algorithm, set coverage and the like. In the 'bus shift scheduling optimization research based on improved genetic-simulated annealing algorithm' by Rong Qing et al, the improved genetic-simulated annealing algorithm is provided in combination with the benefits of both parties of the bus enterprise and the passengers, Jingteng et al considers a plurality of constraints including departure interval ranges in different periods, limitation of the number of available vehicles and constraint of continuation mileage of the pure electric bus in the 'pure electric bus schedule and vehicle shift scheduling plan integral optimization' and adopts a multi-target particle swarm optimization to solve, an optimal solution set of a model is found based on multi-target priority, and a solution of a coding method representation problem is designed in the 'bus shift scheduling method based on the simulated annealing algorithm' by Zhan et al; then, designing an understood evaluation method; finally, a simulated annealing algorithm is proposed to obtain an excellent solution of the problem. However, the above paper does not consider whether the labor time of the driver meets the requirement of the enterprise and whether the driver can be saved to some extent on the basis of saving the vehicle.
Disclosure of Invention
Aiming at the problems and the defects of the current regional scheduling technology, the invention provides a scheduling method for reasonably allocating drivers on the basis of the existing vehicle scheduling scheme, which maximizes the utilization rate of the drivers and ensures that the labor time of the drivers does not exceed the given working time of the public transport enterprises on the basis of fully considering the minimized vehicle use.
The technical scheme adopted for achieving the purpose is a vehicle driver scheduling method in the same dispatching room based on multi-chain type search, and the method comprises the following steps.
(1) Firstly, a vehicle shift feasible solution is searched based on a greedy tabu search algorithm.
(2) And iteratively updating according to the limiting factors of the public transport enterprise to find a vehicle scheduling feasible solution which meets the requirements better. Limiting factors of public transportation enterprises include: whether the non-simultaneous transmission and reception phenomenon is limited, whether the maximum task load of the vehicle is present, and whether the vehicle is allowed to be transmitted at the same position.
(3) And searching an optimal feasible solution according to the minimum loss cost to finally generate a feasible vehicle shift scheduling scheme.
(4) The bus enterprise appoints the maximum daily mileage of a driver to generate an initial solution for the driver to shift.
(5) And generating a driver shift candidate set meeting the constraint condition by adopting a chain search for the vehicle shift feasible scheme.
(6) And generating a final feasible scheme for the driver to shift according to the minimized driver cost.
The chain search comprises the following steps.
(1) The public transportation enterprise self-defines and determines the maximum mileage of a driver all day and determines the floating index and simultaneously designates the operation mileage of a line needing chain type search.
(2) And acquiring an optimal scheduling scheme by establishing a multi-chain searched vehicle scheduling model in a same scheduling room.
(3) The part which accords with the mileage of a driver in the vehicle shift scheduling scheme is removed, and the phenomenon of separating people from the vehicle is avoided as less as possible.
(4) At the moment, a greedy tabu algorithm is adopted to carry out a vehicle shift scheduling model, and a candidate set is generated.
(5) An optimal driver shift schedule is generated by minimizing the number of drivers given constraints.
And (3) generating an initial solution:
Figure BDA0002490502650000031
Figure BDA0002490502650000032
wherein d isqRepresenting the total daily workload of a driver entered by a public transportation enterprise. w is aqTo determine if the penalty for a given driver's full day workload is exceeded, where inf is infinite, αqRepresenting whether the selected driver shift chain meets the given requirements; the initial solution of the driver shift can be obtained preliminarily through the algorithm, and the initial solution can minimize the number of drivers.
Establishing a main function of a multi-chain type searched dispatching model Min of the dispatching room vehicle, establishing the multi-chain type searched dispatching model Min of the dispatching room vehicle, and performing the steps of establishing a vehicle scheduling model in the first step and establishing a driver scheduling model in the second step. Let station D ═ D1，D2，...，DmThe station number of the multi-line is expressed, and the task of the shift T is made to be { T }1，T2，...，TnDenotes the shift number of one line, let line L ═ L1，L2，...，LkDenoted as lines; in this case, it is assumed that the number of generated shift chains is Q, and the shift chain specifying information B is { B }1，B2，...，Bq}；C1,C2,C3Respectively representing the cost of travel between shifts, the cost of non-simultaneous transmission and reception, and the cost of exceeding the maximum task volume.
Figure BDA0002490502650000041
Figure BDA0002490502650000042
The Min primary function is primarily to minimize vehicle usage based on factors that give constraints such as whether non-simultaneous transmission and reception is allowed, whether the maximum mission capacity of the vehicle is limited, etc. The first constraint condition is whether the non-simultaneous transmission and reception phenomenon is allowed, the second constraint condition is whether the maximum task amount of the vehicle is limited, the third constraint condition is the maximum operation shift total amount of the vehicle allowed on the basis of limiting the maximum task amount, wherein INF is an arbitrarily specified maximum value, and the fourth constraint condition is whether the non-simultaneous transmission and reception phenomenon is limited.
The driver scheduling model is established, and the maximum labor efficiency of the driver and the minimum number of the driver are mainly considered under the conditions that the driver scheduling model accords with the policies of the public transportation enterprises and the sufficient rest time of the driver is ensured:
Figure BDA0002490502650000043
Figure BDA0002490502650000044
Figure BDA0002490502650000045
wherein xqRepresenting the turnaround time of shift q, eqRepresenting the rest period after execution of shift q, cijRepresenting the loss cost of driver j to perform shift i, βjRepresenting whether the selected driver shift chain meets the given requirements, the driver shift scheduling model is a multi-objective function, wherein the Min.Z primary function is to maximize the labor efficiency of the driver, Min.NjThe main function is to minimize the number of drivers. The first constraint condition is mainly to meet regional requirements of the bus enterprise, the second constraint condition is to indicate whether the bus number j is selected, and the third constraint condition is to ensure that the shift i can only be executed by one driver in the task.
Technical effects
In the process of dispatching in the multi-line area, the continuity of the same line is mainly considered, and frequent crossing of the multiple lines on the same vehicle is avoided as much as possible, which is not beneficial to the work of a driver. This increases the difficulty of the driver's labor to some extent. However, the product considers the continuity of the same line in the design process and avoids the intersection of different lines as much as possible. This improves the performability between shifts.
The product mainly solves the problem of scheduling in a multi-line co-scheduling room. Therefore, the characteristic of the regional scheduling problem of multiple lines is combined, so that the product can save vehicles to a certain extent compared with single-line scheduling. This can greatly save resources of public transportation enterprises.
The multi-line zone scheduling techniques currently available are not fully implemented in conjunction with the characteristics of the vehicle and the driver. The product fully considers the problems of labor time and labor efficiency of drivers at the design position. The public transport enterprise can carry out the quantity of saving vehicle and driver of certain degree through nimble parameter of setting according to the actual conditions of self.
Drawings
FIG. 1 is a comparison graph of an original vehicle shift schedule versus a chain searched co-scheduled room vehicle shift schedule.
Fig. 2 is a detailed flow diagram of a co-scheduled room vehicle shift based on a multi-chain search.
Fig. 3 is a diagram of a conventional manual shift arrangement system between conventional 312 and 312 areas.
Fig. 4 is a 312, 312 interval chain shift system diagram.
Detailed Description
The bus scheduling and the driver scheduling plan are compiled by considering various factors, the executable maximum shift amount of each part is mainly considered in the vehicle scheduling process, and whether the phenomenon of non-simultaneous transmission and reception is allowed or not is considered if the condition of departure is included in the vehicle scheduling process. In the process of scheduling drivers, the maximum working time and the rest time of the drivers are mainly considered, and the labor efficiency of the drivers is improved as much as possible on the premise of not violating the regulations of public transport enterprises.
For nearly half a century, most of public transport enterprises in China adopt a driver shift mode bound with people and vehicles. People and vehicles are bound, namely, one driver only runs one vehicle, the mode has the advantages of facilitating enterprise management and dividing responsibility, but the defects are obvious that the labor efficiency of the driver is low and the resources of the required public transportation enterprise are more.
1.1 Co-scheduling technical problem description of vehicle scheduling in dispatching room based on multi-chain search
The regional vehicle scheduling technology based on multi-chain search mainly provides a feasible scheme for vehicle scheduling and driver scheduling on the premise of meeting the limiting conditions of public transport enterprises to minimize the vehicle usage and maximize the labor efficiency of drivers.
Since the product mainly discusses a minimized vehicle shift schedule and a driver shift schedule based on a man-vehicle separation mode.
1.2 Co-scheduling room vehicle scheduling technique based on multi-chain search
1.2.1 principle of the Algorithm
The regional vehicle scheduling technology is mainly realized by adopting a chain search and greedy tabu search algorithm. The basic principle of the algorithm is as follows: (1) firstly, searching a feasible vehicle shift scheduling solution based on a greedy tabu search algorithm; (2) according to the limiting factors of public transport enterprises, for example: whether non-simultaneous transmission and reception phenomena are limited, whether the maximum task amount of the vehicle is present, whether iterative updating is allowed to be carried out on factors that the vehicle is transmitted at the same position and the like to find a feasible solution for vehicle scheduling which meets requirements better; (3) searching an optimal feasible solution according to the minimum loss cost to finally generate a feasible vehicle shift scheduling scheme; (4) the bus enterprise appoints the maximum daily mileage of a driver to generate an initial solution for the driver to shift; (5) generating a driver shift candidate set which meets the constraint condition by adopting chain search for a vehicle shift feasible scheme; (6) and generating a final feasible scheme for the driver to shift according to the minimized driver cost.
Regarding the 'limiting factor' in the step (2), the bus enterprises in different areas have different policies, so that the shift arrangement results required by the bus enterprises in different areas have great difference, for example, some areas of enterprises can allow the phenomena of non-simultaneous transmission and simultaneous reception and empty driving to occur in the shift arrangement process, but the shift arrangement policy in some areas strictly controls the phenomena of non-simultaneous transmission and simultaneous reception. Therefore, different limiting factors have great influence on the result of scheduling, and the product can allow the user to change the limiting factors according to the actual requirements of the user. And the limitations of considering these factors at the same time are also a highlight of the present system.
The generation procedure for the initial solution in step (4) is as follows:
the product mainly selects two vehicles at random through a chain technology and forms a proper amount of drivers, and the step mainly aims to reduce the number of the drivers as much as possible, and a specific algorithm is as follows:
Figure BDA0002490502650000071
Figure BDA0002490502650000072
wherein d isqRepresenting the total daily workload of a driver entered by a public transportation enterprise. w is aqTo the cost of whether the total daily workload of a given driver is exceededLoss, where inf is infinite, αqRepresenting whether the selected driver shift chain meets the given requirements.
The driver shift initial solution can be obtained preliminarily through the algorithm, the initial solution can minimize the number of drivers to a certain extent, but in practice, part of the drivers still exceed the given task amount, namely, part of the drivers fatigue driving.
The chain searching technology is a process for reasonably distributing drivers on the basis of the existing vehicle shift arrangement scheme.
If the driver is scheduled according to the original vehicle scheduling scheme as shown in fig. 1, the part 1 and the part 2 need 4 drivers in total to perform the current shift, but it can be found that if four drivers are needed for two parts, the labor time of the drivers is too short, which may cause resource waste of the public transportation enterprise to a certain extent. At the moment, the scheduling schemes of all parts are searched in a chain mode, and driver scheduling is recombined on the premise of appointing the maximum labor time of the driver. It can be found that under the human-vehicle separation mode, only three drivers are needed to complete the whole task amount of the two parts, thereby maximizing the benefit of the drivers to a certain extent and being more beneficial to saving the cost of the drivers.
While by observing the positions 3, 4 it can be seen that the two positions require a total of two drivers to complete the entire task. Although fewer drivers are needed, the labor time of the drivers is too long, driving safety is not facilitated, and meanwhile labor laws are violated, and the chain search can find that the two parts can realize that three drivers execute the current-day plan on the premise that all constraint conditions are met through certain combination. Although compare in original scheme and used a driver more, but can greatly reduced driving danger probability like this, promote driver's occupation comfort level simultaneously.
The specific principle of chain search is as follows:
(1) the method comprises the steps that a public transportation enterprise self-defines and determines the maximum mileage of a driver all day, and determines the floating indexes and simultaneously designates the operating mileage of a line needing chain type search;
(2) acquiring a better vehicle scheduling scheme through a vehicle scheduling model;
(3) after the better vehicle scheduling scheme is obtained, the part which meets the mileage of a driver in the vehicle scheduling scheme is removed, and the phenomenon of separation of people and vehicles is avoided as less as possible;
(4) at the moment, a greedy taboo algorithm based driver scheduling model is adopted to generate a candidate set;
(5) an optimal driver shift schedule is generated by minimizing the number of drivers given constraints.
The specific flow of the scheduling technique for vehicles in the same dispatching room based on the multi-chain search is shown in fig. 2.
1.2.2 Co-dispatching Room vehicle dispatching model based on Multi-chain search
The method comprises the steps of establishing a multi-chain type search vehicle scheduling model in a same scheduling room, wherein the multi-chain type search vehicle scheduling model is mainly performed in two steps, namely, establishing a vehicle scheduling model in the first step, and establishing a driver scheduling model in the second step. Let station D ═ D1，D2，....，DmThe station number of the multi-line is expressed, and the task of the shift T is made to be { T }1，T2，...，TnDenotes the shift number of one line, let line L ═ L1，L2，..，LkDenoted as lines. In this case, it is assumed that the number of generated shift chains is Q, and the shift chain specifying information B is { B }1，B2，...，Bq}. At the same time C1,C2,C3Respectively representing the cost of travel between shifts, the cost of non-simultaneous transmission and reception, and the cost of exceeding the maximum task volume.
The vehicle shift scheduling model is as follows:
Figure BDA0002490502650000091
Figure BDA0002490502650000092
the Min function mainly refers to a vehicle scheduling model, and the Min main function is mainly used for minimizing the vehicle usage amount on the basis of factors such as whether non-simultaneous transmission and reception are allowed or not, whether the maximum task amount of the vehicle is limited or not and the like. The first constraint condition is whether the non-simultaneous transmission and reception phenomenon is allowed to occur, the second constraint condition is whether the maximum task amount of the vehicle is limited, the third constraint condition is the maximum operation total number of shifts of the vehicle allowed on the basis of limiting the maximum task amount, wherein INF is an arbitrarily specified maximum value, and the fourth constraint condition is whether the non-simultaneous transmission and reception phenomenon is limited.
Driver scheduling model: the maximum labor efficiency of the drivers and the minimum number of the drivers under the conditions of meeting the policies of the public transportation enterprises and ensuring the sufficient rest time of the drivers are mainly considered in the establishment of the driver scheduling model.
Figure BDA0002490502650000101
Figure BDA0002490502650000102
Figure BDA0002490502650000103
Wherein xqRepresenting the turnaround time of shift q, eqRepresenting the rest period after execution of shift q, cijRepresenting the loss cost of driver j to perform shift i, βjRepresenting whether the selected driver shift chain meets the given requirements, the driver shift scheduling model is a multi-objective function, wherein the Min.Z primary function is to maximize the labor efficiency of the driver, Min.NjThe main function is to minimize the number of drivers. The first constraint condition is mainly to meet regional requirements of the bus enterprise, the second constraint condition is to indicate whether the bus number j is selected, and the third constraint condition is to ensure that the shift i can only be executed by one driver in the task.
Compared with the common regional scheduling technology, the product maximizes the utilization rate of the driver on the basis of fully considering the minimized vehicle use and ensures that the labor time of the driver does not exceed the given working time of the public transport enterprise. The advantages of the product are mainly described in three aspects of executive performance, vehicle saving and driver saving of the shift.
In the process of dispatching in the multi-line area, the continuity of the same line is mainly considered, and frequent crossing of the multiple lines on the same vehicle is avoided as much as possible, which is not beneficial to the work of a driver. This increases the difficulty of the driver's labor to some extent. However, the product considers the continuity of the same line in the design process and avoids the intersection of different lines as much as possible. This improves the performability between shifts.
The efficient and intelligent matching of the multi-line vehicle driver and the multi-line operation plan can be realized by changing the shift in one key, and compared with the traditional manual arrangement of the vehicle driver aiming at the multi-line operation plan in the public transportation enterprise, the efficient and intelligent matching and the time saving are realized.
Compare traditional round of preface gear shift and can reduce vehicle driver waiting time on the spot, improve the vehicle time on duty, and then can improve vehicle driver utilization ratio and from the current circuit save vehicle driver in joining in marriage the car, and the bus and the company machine that get down from many current circuits can go to run customized public transit, net appointment bus, bus telephone appointment or use on putting into the bus line of newly-opening, thereby reduce the human cost of enterprise, purchase the car cost and improve bus enterprise economic benefits.
Case (2): taking the interval between the lines 312 and 312 as an example, the traditional manual shift and chain shift comparative analysis is performed.
The traditional 312, 312 interval traditional manual shift is as in fig. 3. 312. The 312-interval chain shift is as shown in FIG. 4.
The conventional manual shift versus chain shift vehicle usage is shown in table 1 below.
Traditional manual shift arrangement) Chain type shift vehicle (bench) Saving vehicle (bench)
19 16 3
312 analysis of the number of shifts between the chain 312 zones is given in table 2 below.
Number of line shifts Number of chain shifts Number of total shifts Chain duty ratio
60 21 81 25.93％

Claims (5)

1. A vehicle driver scheduling method in the same dispatching room based on multi-chain search is characterized by comprising the following steps:
step 1: firstly, searching a feasible vehicle shift scheduling solution based on a greedy tabu search algorithm;
step 2: iteratively updating according to the limiting factors of the public transport enterprise to find a vehicle scheduling feasible solution which meets the requirements better;
and step 3: searching an optimal feasible solution according to the minimum loss cost to finally generate a feasible vehicle shift scheduling scheme;
and 4, step 4: the bus enterprise appoints the maximum daily mileage of a driver to generate an initial solution for the driver to shift;
and 5: generating a driver shift candidate set which meets the constraint condition by adopting chain search for a vehicle shift feasible scheme;
step 6: generating a final feasible scheme for the driver to shift according to the minimized driver cost;
the chain search comprises the following steps:
1) the method comprises the steps that a public transportation enterprise self-defines and determines the maximum mileage of a driver all day, and determines the floating indexes and simultaneously designates the operating mileage of a line needing chain type search;
2) acquiring an optimal scheduling scheme by establishing a multi-chain searched vehicle scheduling model in a same scheduling room;
3) the part which accords with the mileage of a driver in the vehicle shift scheduling scheme is removed, so that the phenomenon of separation of people and vehicles is avoided as less as possible;
4) at the moment, a greedy tabu algorithm is adopted to carry out a vehicle shift scheduling model, and a candidate set is generated;
5) an optimal driver shift schedule is generated by minimizing the number of drivers given constraints.
2. The method for scheduling drivers of vehicles in the same dispatching room based on multi-chain search as claimed in claim 1, wherein the limiting factors of the public transportation enterprises in step 2 comprise: whether the non-simultaneous transmission and reception phenomenon is limited, whether the maximum task load of the vehicle is present, and whether the vehicle is allowed to be transmitted at the same position.
3. The method for driver's scheduling in the same dispatching room based on multi-chain search as claimed in claim 1, wherein the generation process of the initial solution in step 4 is as follows:
Figure FDA0002490502640000021
Figure FDA0002490502640000022
wherein d isqRepresenting the total daily workload of a driver entered by a public transportation enterprise. w is aqTo determine if the penalty for a given driver's full day workload is exceeded, where inf is infinite, αqRepresenting whether the selected driver shift chain meets the given requirements; the initial solution of the driver shift can be obtained preliminarily through the algorithm, and the initial solution can minimize the number of drivers.
4. The method for driver's scheduling in the same dispatching room based on multi-chain search as claimed in claim 1, wherein the step 6 is implemented by establishing a main function of a multi-chain search scheduling model Min for the vehicle in the same dispatching room, and making station D ═ { D ═ D1，D2，...，DmThe station number of the multi-line is expressed, and the task of the shift T is made to be { T }1，T2，...，TnDenotes the shift number of one line, let line L ═ L1，L2，...，LkDenoted as lines; in this case, it is assumed that the number of generated shift chains is Q, and the shift chain specifying information B is { B }1，B2，...，Bq}；C1,C2,C3Respectively representing the cost of driving between shifts, the cost of non-simultaneous transmission and reception and the cost exceeding the maximum task amount;
Figure FDA0002490502640000023
Figure FDA0002490502640000024
the Min primary function is to minimize vehicle usage based on given constraints; the first constraint condition is whether the non-simultaneous transmission and reception phenomenon is allowed, the second constraint condition is whether the maximum task amount of the vehicle is limited, the third constraint condition is the maximum operation shift total amount of the vehicle allowed on the basis of limiting the maximum task amount, wherein INF is an arbitrarily specified maximum value, and the fourth constraint condition is whether the non-simultaneous transmission and reception phenomenon is limited.
5. The method of claim 4, wherein the step of establishing the multi-chain search co-dispatching-room vehicle driver scheduling model further comprises establishing a driver scheduling model, mainly considering maximizing the labor efficiency of the driver and minimizing the number of drivers under the conditions of meeting the policies of the public transportation enterprises and ensuring sufficient rest time of the driver:
Figure FDA0002490502640000031
Figure FDA0002490502640000032
Figure FDA0002490502640000033
wherein xqRepresenting the turnaround time of shift q, eqRepresenting the rest period after execution of shift q, cijRepresenting the loss cost of driver j to perform shift i, βjRepresenting whether the selected driver shift chain meets the given requirements, the driver shift scheduling model is a multi-objective function, wherein the Min.Z primary function is to maximize the labor efficiency of the driver, Min.NjThe primary function is to minimize the number of drivers; the first constraint condition is mainly to meet regional requirements of the bus enterprise, the second constraint condition is to indicate whether the bus number j is selected, and the third constraint condition is to ensure that the shift i can only be executed by one driver in the task.
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