CN113888272B - Commuting network vehicle-contract dispatching method based on stable matching theory - Google Patents
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Abstract
The invention discloses a commute network about car dispatching method based on a stable matching theory, which allows a network about car to provide service for a single demand, secondly, the network about car service meets the time window and cost constraint of passengers, thirdly, the preference relation between the network about car and the passengers is established, and finally, the stable matching model of the passengers and the network about car is established; and solving a stable matching model of the passengers and the network vehicle by using a Gale-Shapley algorithm to determine a network vehicle dispatching scheme and a path. The commute network vehicle order dispatching method based on the stable matching theory solves the problem that the traditional dispatching method lacks flexibility to a certain extent, considers the selection preference of passengers and network vehicle drivers, and has stability in matching; the satisfaction degree and the matching success rate of passengers and network taxi drivers can be effectively improved.
Description
Technical Field
The invention relates to a network vehicle appointment method, in particular to a commute network vehicle appointment method based on a stable matching theory.
Background
In the background of the development of the Internet plus and the development of the sharing economy, the industry of network reservation taxis (called network taxi for short) is developed and rapidly expanded, and a commuting mode based on sharing is accepted by the masses. Although the platform considers factors such as the receiving distance during dispatching, the individual selection preference information of passengers and network taxi drivers is usually ignored mainly according to the global optimal principle, so that the selection requirements of the passengers and network taxi drivers cannot be fully met. For commute needs, which are reciprocal, both passengers and net-bound car drivers can accumulate experience and learn certain information over multiple matches. Neglecting the personalized selection needs of passengers and net-bound car drivers not only reduces their satisfaction with the platform, but also results in an unstable match, which passengers and net-bound car drivers may not accept or use the matching system in future trips, resulting in loss of social benefits. Therefore, considering the matching stability in the dispatching process is particularly important for sustainable development of the network taxi platform.
In summary, the following three points of the current internet appointment form are not enough. (1) The conventional system optimal mode dispatch results in that the selection preference of partial passengers or network taxi drivers is not satisfied; (2) the traditional form assignment mode causes unstable matching; (3) Traditional dispatch does not adequately consider the gender requirements of shared commute.
Disclosure of Invention
In order to make up the defects of the prior art, the invention provides a commute network vehicle-about dispatching method based on a stable matching theory.
The technical scheme adopted by the invention is as follows:
A commute network about car dispatch method based on a stable matching theory is characterized in that a network about car is allowed to provide service for a single demand, secondly, the network about car service meets the time window and cost constraint of passengers, thirdly, the preference relation between the network about car and the passengers is established, and finally, a stable matching model of the passengers and the network about car is established; solving a stable matching model of the passengers and the network vehicle by using a Gale-Shapley algorithm, and determining a network vehicle dispatching scheme and a path; the solving method specifically comprises the following steps:
(1) Defining a graph on which the model is based;
(2) Defining a preference relationship;
(3) Constructing a stable matching model;
(4) The solution was performed using the Gale-Shapley algorithm.
Further, the commute network vehicle assignment method based on the stable matching theory is characterized by comprising the following steps of: the step (1) comprises the following steps:
(1-1) defining a model based on the graph in the form of:
d is a network taxi driver set, and R is a passenger set; the net car driver i and the passenger j meet the following constraint, and then the net car driver i and the passenger j establish a feasible edge;
(1-2) defining a time window constraint in the form of:
The first constraint indicates that the passenger can be serviced when the net taxi driver reaches the passenger's origin; the second constraint indicates that the passenger was delivered before the latest arrival time; the third constraint indicates that the net jockey car driver arrives at the destination before the latest arrival time; e i is the earliest departure time; t ab is the time from node a to node b; τ j is the time the net taxi driver arrives at the node; l j is the latest arrival time; o i is the starting point; g i is the endpoint;
(1-3) defining a cost constraint in the form of:
the first constraint indicates that the total passenger commute cost does not exceed an upper limit; the second constraint indicates that the net jockey driver total cost does not exceed an upper limit; when the vehicle driver i is matched for the passenger j net vehicle, the commuting cost of the passenger is reduced; /(I) When the net car driver i of the passenger j is matched, the commute cost of the net car driver is increased; ρ j is the maximum acceptable commute cost.
Further, the commute network vehicle assignment method based on the stable matching theory is characterized by comprising the following steps of: the step (2) comprises the following steps:
(2-1) defining a ranking index in the form:
The first index is the total commute cost of the passengers, including time cost and fare; the second index is the total commute cost of the net-bound vehicle driver, including the driving cost and the time cost, and deducts the payment of the vehicle fee by the passengers; alpha is the cost per unit time; Paying a fare for the passenger; c ij is the driving expense when the driver i of the passenger j net vehicle is matched;
(2-2) defining preference relationships in the form of:
The method for generating the preference relation of the passengers to the network taxi drivers is that the commute cost relation of the passengers j matched with the network taxi drivers i and i' is set as that Then the preference relationship is i > j i'; the method for generating the preference relation of the net appointment vehicle driver to the passengers is that if the commute cost relation of the net appointment vehicle driver i matched with the passengers j and j' is/>Then the preference relationship is j > i j'.
Further, the commute network vehicle assignment method based on the stable matching theory is characterized by comprising the following steps of: the step (3) comprises the following steps:
(3-1) constructing a stable matching model according to the characteristics of the present problem, setting an objective function as Wherein the first summation term/>Representing the total commute cost of the matched passenger and net taxi driver, the second summation term/>And a third summation termRepresenting the total commute costs of the unmatched passengers and net taxi drivers; x ij is a 0-1 variable, which is 1 when passenger i and net bus driver j are matched, or 0;
(3-2) defining an assignment constraint in the form of:
The first constraint represents that one passenger can only match one net restraint vehicle driver; the second constraint indicates that a net taxi driver can only match one passenger; epsilon R (i) is a passenger set that establishes a viable edge with the net taxi driver i; epsilon D (j) is a net taxi driver set which establishes a feasible edge with passenger j;
(3-3) defining a stability constraint in the form:
when passenger j and net taxi driver i form a matched pair, X ij = 1, Thus, it is possible to obtain/>When passenger j and net taxi driver i do not form a matched pair, X ij =0; necessarily require/>And/>With the result that passenger j matches the more preferred net jockey driver i 'or net jockey driver i matches the more preferred passenger j', or both passenger j and net jockey driver i match the more preferred object.
Further, the commute network vehicle assignment method based on the stable matching theory is characterized by comprising the following steps of: the step (4) comprises the following steps:
(4-1) solving a passenger-to-net vehicle stable matching scheme, namely deciding a passenger-to-net vehicle assignment and driving path, by using a Gale-shape algorithm.
The invention has the following beneficial effects:
(1) The commute network vehicle order dispatching method based on the stable matching theory solves the problem that the traditional dispatching method lacks flexibility to a certain extent;
(2) The commute network vehicle-about dispatching method based on the stable matching theory considers the selection preference of passengers and network vehicle-about drivers, and the matching has stability;
(3) The commute network vehicle order dispatching method based on the stable matching theory can effectively improve satisfaction degree of passengers and network vehicle drivers and matching success rate.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments.
Example 1.
A commute network vehicle order dispatching method based on a stable matching theory comprises the following steps:
1) The definition model is based on the graph in the following form:
D is a network taxi driver set, and R is a passenger set; if the net taxi driver i and the passenger j meet the following constraint, the net taxi driver i and the passenger j establish a feasible edge;
Defining a time window constraint in the form of:
The first constraint indicates that the passenger can be serviced when the net driver reaches the passenger's origin. The second constraint indicates that the passenger was delivered before the latest arrival time. The third constraint indicates that the net driver arrives at the destination before the latest arrival time. e i is the earliest departure time; t ab is the time from node a to node b; τ j is the time the net taxi driver arrives at the node; l j is the latest arrival time; o i is the starting point; g i is the endpoint.
Cost constraints are defined in the form:
The first constraint indicates that the total passenger commute cost does not exceed an upper limit. The second constraint indicates that the net jockey total cost to the driver does not exceed the upper limit. When the vehicle driver i is matched for the passenger j net vehicle, the commuting cost of the passenger is reduced; /(I)When the net car driver i of the passenger j is matched, the commute cost of the net car driver is increased; ρ j is the maximum acceptable commute cost.
2) Definition of the definition preference relationship, the form is as follows:
Defining a ranking index in the form of:
The first index is the total commute cost of the passengers, including time cost and fare. The second index is the net bus driver total commute cost, including driving cost and time cost, and deducts the passenger payment of the bus fee. Alpha is the cost per unit time; Paying a fare for the passenger; c ij is the driving cost when the passenger j net car driver i is matched.
Preference relationships are defined in the form:
the method for generating the preference relation of the passengers to the network taxi drivers is that if the commute cost relation of the passengers j matched with the network taxi drivers i and i' is that Then the preference relationship is i > j i'; the method for generating the preference relation of the net appointment vehicle driver to the passengers is that if the commute cost relation of the net appointment vehicle driver i matched with the passengers j and j' is/>Then the preference relationship is j > i j';
3) A stable matching model is constructed in the following form:
according to the characteristics of the problem, a stable matching model is constructed, and an objective function is set as Wherein the first summation term/>Representing the total commute cost of the matched passenger and net taxi driver, the second summation term/>And a third summation termRepresenting the total commute costs of the unmatched passengers and net taxi drivers; x ij is a 0-1 variable, which is 1 when passenger i and net bus driver j are matched, or 0;
defining assignment constraints in the form:
The first constraint represents that a passenger can only match a net restraint vehicle driver. The second constraint indicates that a net driver can only match one passenger. Epsilon R (i) is a passenger set that establishes a viable edge with the net taxi driver i; epsilon D (j) is a set of net taxi drivers that establish a viable edge with passenger j.
Stability constraints are defined in the form:
when passenger j and net taxi driver i form a matched pair, X ij = 1, Thus, it is possible to obtain/>When passenger j and net car driver i do not form a matched pair, X ij =0. Necessarily require/>And/>With the result that passenger j matches the more preferred net jockey driver i 'or net jockey driver i matches the more preferred passenger j', or both passenger j and net jockey driver i match the more preferred object.
4) Solving by using Gale-Shapley algorithm, the form is as follows:
And solving a stable matching scheme of the passengers and the network about vehicles by using a Gale-Shapley algorithm, namely deciding the assignment and driving paths of the passengers and the network about vehicles.
The foregoing is merely a preferred embodiment of the present application and is not intended to limit the scope of the present application, and various modifications of the equivalent forms of the present application will fall within the scope of the appended claims after reading the present application.
Claims (2)
1. A commute network about car dispatch method based on a stable matching theory is characterized in that a network about car is allowed to provide service for a single demand, secondly, the network about car service meets the time window and cost constraint of passengers, thirdly, the preference relation between the network about car and the passengers is established, and finally, a stable matching model of the passengers and the network about car is established; solving a stable matching model of the passengers and the network vehicle by using a Gale-Shapley algorithm, and determining a network vehicle dispatching scheme and a path; the solving method specifically comprises the following steps:
(1) Defining a graph on which the model is based;
(2) Defining a preference relationship;
(3) Constructing a stable matching model;
(4) Solving by using a Gale-Shapley algorithm;
(1-1) defining a model based on the graph in the form of:
d is a network taxi driver set, and R is a passenger set; the net car driver i and the passenger j meet the following constraint, and then the net car driver i and the passenger j establish a feasible edge;
(1-2) defining a time window constraint in the form of:
The first constraint indicates that the passenger can be serviced when the net taxi driver reaches the passenger's origin; the second constraint indicates that the passenger was delivered before the latest arrival time; the third constraint indicates that the net jockey car driver arrives at the destination before the latest arrival time; e i is the earliest departure time; t ab is the time from node a to node b; τ j is the time the net taxi driver arrives at the node; l j is the latest arrival time; o i is the starting point; g i is the endpoint;
(1-3) defining a cost constraint in the form of:
the first constraint indicates that the total passenger commute cost does not exceed an upper limit; the second constraint indicates that the net jockey driver total cost does not exceed an upper limit; when the vehicle driver i is matched for the passenger j net vehicle, the commuting cost of the passenger is reduced; /(I) When the net car driver i of the passenger j is matched, the commute cost of the net car driver is increased; ρ j is the maximum acceptable commute cost;
(2-1) defining a ranking index in the form:
The first index is the total commute cost of the passengers, including time cost and fare; the second index is the total commute cost of the net-bound vehicle driver, including the driving cost and the time cost, and deducts the payment of the vehicle fee by the passengers; alpha is the cost per unit time; Paying a fare for the passenger; c ij is the driving expense when the driver i of the passenger j net vehicle is matched;
(2-2) defining preference relationships in the form of:
The method for generating the preference relation of the passengers to the network taxi drivers is that the commute cost relation of the passengers j matched with the network taxi drivers i and i' is set as that Then the preference relationship is i > j i'; the method for generating the preference relation of the net appointment vehicle driver to the passengers is that if the commute cost relation of the net appointment vehicle driver i matched with the passengers j and j' is/>Then the preference relationship is j > i j';
(3-1) constructing a stable matching model according to the characteristics of the present problem, setting an objective function as Wherein the first summation term/>Representing the total commute cost of the matched passenger and net taxi driver, the second summation term/>And a third summation termRepresenting the total commute costs of the unmatched passengers and net taxi drivers; x ij is a 0-1 variable, which is 1 when passenger i and net bus driver j are matched, or 0;
(3-2) defining an assignment constraint in the form of:
The first constraint represents that one passenger can only match one net restraint vehicle driver; the second constraint indicates that a net taxi driver can only match one passenger; epsilon R (i) is a passenger set that establishes a viable edge with the net taxi driver i; epsilon D (j) is a net taxi driver set which establishes a feasible edge with passenger j;
(3-3) defining a stability constraint in the form:
when passenger j and net taxi driver i form a matched pair, X ij = 1, Thus, it is possible to obtain/>When passenger j and net taxi driver i do not form a matched pair, X ij =0; necessarily require/>And/>With the result that passenger j matches the more preferred net jockey driver i 'or net jockey driver i matches the more preferred passenger j', or both passenger j and net jockey driver i match the more preferred object.
2. The commute network vehicle dispatch method based on stable matching theory of claim 1, wherein the method comprises the following steps: the step (4) comprises the following steps:
(4-1) solving a passenger-to-net vehicle stable matching scheme, namely deciding a passenger-to-net vehicle assignment and driving path, by using a Gale-shape algorithm.
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