Team travel resource allocation method and system based on multi-source data

Abstract

The application discloses a team travel resource allocation method and system based on multi-source data, and belongs to the technical field of travel management, and comprises the following steps: obtaining team travel task information, wherein the team travel task information comprises a member list, a post type of each member and a project dependency relationship; constructing a project network diagram according to the project dependency relationship, wherein the project network diagram comprises a plurality of task nodes and dependency edges between the nodes; calculating a role importance parameter of each member in the team travel task; determining an allocation priority of each member according to the role importance parameter; obtaining available traffic resource information corresponding to a travel destination; and allocating traffic resources to each member in turn according to the allocation priority from high to low priority. The adaptability, economy and task guarantee capability of team travel resource allocation are significantly improved.

Claims

1. A method for allocating team travel resources based on multi-source data, characterized in that, Includes the following steps: Obtain team business trip task information, which includes a member list, the job type of each member, and project dependencies; A project network graph is constructed based on the project dependencies, and the project network graph includes multiple task nodes and dependency edges between nodes; The role importance parameter of each member in the business trip task is calculated. The role importance parameter is obtained by extracting the critical path dependency of the member in the project network diagram. The critical path dependency is determined by the criticality of the path of the task node under the member's responsibility and the topological position of the node in the path. The critical path dependency is weighted and fused with the preset basic weight of the job type to calculate the role importance parameter. The critical path dependency is determined in the following way: Identify all critical paths in the project network diagram, where the critical path is the path with the longest project duration; For each member's assigned task node, calculate the probability that the node is located on the critical path, as well as the forward and backward float times of the node on the critical path. The critical path dependency is calculated based on the probability value, forward float time, and backward float time. Nodes with higher probability values ​​and smaller float times have higher critical path dependencies. The role importance parameter is further modified based on the degree of collaboration between members. The degree of collaboration is determined by the sum of the weights of the dependency edges between nodes extracted from the project dependency relationship. The greater the sum of the weights of the dependency edges between a member and other members, the greater the positive correction of its role importance parameter. The allocation priority of each member is determined based on the aforementioned role importance parameters; Obtain available transportation resource information corresponding to the business trip destination. The transportation resource information includes transportation type, transportation schedule, departure time, arrival time, transportation resource level, corresponding number of available seats, and cost information. According to the allocation priority, transportation resources are allocated to each member in descending order of priority. Each member is allocated transportation resources that meet their task time constraints and have the highest overall matching degree. The overall matching degree is calculated based on the matching degree between the member's task time window and the arrival time of the transportation bus, the matching degree between the transportation resource level and the role importance parameter, and the transportation resource cost.

2. The method according to claim 1, characterized in that, It also includes a dynamic reallocation step: After the initial allocation is completed, monitor the changes in the remaining traffic resources and the changes in the task status of members in real time; When an allocated resource is detected to be canceled or delayed, or when a member's task time constraints change, a dynamic reallocation operation is triggered. The dynamic reallocation operation is based on the current remaining resources and the unaffected allocated resources. It recalculates the dynamic adjustment factor of the role importance parameter of the affected members and performs the resource reallocation operation according to the adjusted parameters.

3. The method according to claim 2, characterized in that, The resource reallocation operation includes: Construct a set of resource requirements for affected members, which includes the task time window, role importance parameter, and acceptable resource level range for each affected member; A multi-objective optimization algorithm is adopted to generate a globally optimal resource allocation scheme for the affected members with the goal of minimizing the weighted sum of the overall resource cost and the impact of the project critical path. The overall resource cost is the sum of the traffic resource costs of all members in the allocation scheme, and the impact of the project critical path is the degree of impact of the resource allocation scheme on the project critical path duration. Based on the globally optimal resource allocation scheme, corresponding traffic resources are allocated to each affected member.

4. The method according to claim 3, characterized in that, The multi-objective optimization algorithm includes: The resource reallocation operation is modeled as a constrained combinatorial optimization problem, where the decision variables are the matching relationship between each member and each available transportation resource, and the constraints include the task time constraints of the members, the available quantity of resources constraints, and the resource level matching constraints. Solving the combinatorial optimization problem yields a Pareto optimal solution set. Based on the preset overall resource cost weight and the project critical path impact weight, the solution with the smallest weighted sum is selected from the Pareto optimal solution set as the globally optimal resource allocation scheme.

5. The method according to claim 3, characterized in that, When a feasible resource allocation scheme that satisfies the time constraints of all member tasks cannot be obtained through the multi-objective optimization algorithm, a trip fragmentation algorithm is triggered, which includes: The original itinerary is divided into multiple itinerary segments according to the timeline; In the available transportation resource information, match available transportation schedules for each trip segment; then, splice the successfully matched trip segments in chronological order to form an alternative trip plan that meets the task time constraints. Calculate the overall cost coefficient and time deviation coefficient of the alternative travel options, and select the option with the smallest weighted sum of the overall cost coefficient and time deviation coefficient as the final alternative resource combination for that member.

6. The method according to claim 2, characterized in that, The dynamic adjustment factor for the role importance parameter is calculated based on at least one of the following factors: the time urgency of the task status change, the impact of resource changes on the project critical path, and the change in path criticality after the member replans the project network diagram.

7. The method according to claim 1, characterized in that, The overall matching degree is calculated using the following formula: ； in, For members With transportation schedules Overall matching degree For members Task time window and transportation schedule The degree of matching of arrival times, For transportation schedules Resource levels and members The matching coefficient of the role importance parameter. For transportation schedules The matching coefficient between the cost and the preset cost threshold. , and These are preset weighting coefficients.

8. A team travel resource allocation system based on multi-source data, characterized in that, include: The task information acquisition module is used to acquire team business trip task information, which includes a member list, the job type of each member, and project dependencies. The construction module is used to construct a project network graph based on the project dependencies, wherein the project network graph includes multiple task nodes and dependency edges between nodes; The importance calculation module is used to extract the critical path dependency of the member in the project network graph. The critical path dependency is determined by the criticality of the path of the task node under the member's responsibility and the topological position of the node in the path. The critical path dependency is weighted and fused with the preset basic weight of the job type to calculate the role importance parameter. The critical path dependency is determined in the following way: Identify all critical paths in the project network diagram, where the critical path is the path with the longest project duration; For each member's assigned task node, calculate the probability that the node is located on the critical path, as well as the forward and backward float times of the node on the critical path. The critical path dependency is calculated based on the probability value, forward float time, and backward float time. Nodes with higher probability values ​​and smaller float times have higher critical path dependencies. The role importance parameter is further modified based on the degree of collaboration between members. The degree of collaboration is determined by the sum of the weights of the dependency edges between nodes extracted from the project dependency relationship. The greater the sum of the weights of the dependency edges between a member and other members, the greater the positive correction of its role importance parameter. The priority determination module is used to determine the allocation priority of each member based on the role importance parameter; The traffic information acquisition module is used to acquire available traffic resource information corresponding to the business trip destination. The traffic resource information includes traffic type, traffic schedule, departure time, arrival time, traffic resource level, corresponding number of available seats, and cost information. The allocation execution module is used to allocate transportation resources to each member in descending order of priority according to the allocation priority. Specifically, each member is allocated transportation resources that meet their task time constraints and have the highest overall matching degree. The overall matching degree is calculated based on the degree of matching between the member's task time window and the arrival time of the transportation bus, the degree of matching between the transportation resource level and the role importance parameter, and the transportation resource cost.

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