6 results about "Crew scheduling" patented technology

This invention discloses a crew scheduling method, system, and equipment based on multi-dimensional fatigue prediction and TEM optimization, relating to the field of aviation operation control technology. It generates crew member capability parameters by acquiring multi-dimensional flight mission data and performing time alignment and correlation integration; obtains a demand summary result based on the TEM threat knowledge base mapping, calculates the coupling increment by combining the situation-coupled threat map, and forms a situation-enhanced demand summary result; synthesizes basic operational requirements and situation-enhanced requirements into comprehensive capability requirements, and dynamically adjusts them according to a phased dynamic amplification coefficient under unexpected events; generates vulnerability correction parameters based on crew operation adaptation data, and calculates situation-effective maneuverability and cognitive ability; obtains energy state parameters through a fatigue prediction model, defines resilience margin indicators based on situation-effective capability and comprehensive capability requirements, and constructs capability matching constraints to generate a scheduling plan; updates parameters and performs rescheduling and decision chain output when data changes are detected.

The application discloses a crew scheduling method, system and equipment based on multi-dimensional fatigue prediction and TEM optimization, and relates to the technical field of aviation operation control. Multi-dimensional data of a flight task is acquired, time alignment and associated integration are performed, and crew member capability parameters are generated. A demand summary result is obtained based on a TEM threat knowledge base mapping, a coupling increment is calculated in combination with a situation coupling threat graph, a situation enhanced demand summary result is formed, basic operation demand and situation enhanced demand are summarized to form comprehensive capability demand, and dynamic adjustment is performed according to a phased dynamic amplification coefficient under an unexpected event. A vulnerability correction parameter is generated based on crew operation adaptation data, situation effective operating capability and cognitive capability are calculated, an energy state parameter is obtained through a fatigue prediction model, a resilience margin index is defined based on situation effective capability and comprehensive capability demand, capability matching constraints are constructed, a scheduling scheme is generated, and parameters are updated when data changes are monitored, and rescheduling and decision chain output are performed.

This invention provides an intelligent scheduling and configuration method and system for shared vehicle maintenance personnel, relating to the field of shared vehicle technology. Based on a preset time period, it retrieves historical scheduling data of shared vehicles, constructs a scheduling task matching module and a scheduling path generation module, generates a vehicle maintenance scheduling model, obtains user vehicle demand applications and integrates them as batch target application information, generates a single set of scheduling tasks and multiple scheduling paths, wherein each single set of scheduling tasks corresponds one-to-one with the multiple scheduling paths, and achieves intelligent vehicle scheduling and maintenance based on the single set of scheduling tasks and multiple scheduling paths. This invention solves the technical problem that existing shared vehicle maintenance personnel scheduling and configuration methods cannot establish reasonable indicators based on the demand for shared vehicle resources in different times and spaces, leading to unreasonable allocation of maintenance personnel. It achieves multi-model coordination and optimization, performs optimal allocation of maintenance tasks, and achieves the technical effect of improving vehicle utilization and reducing the workload of maintenance personnel.

This application relates to the field of intelligent adjustment and compilation technology for train crew routes, and provides a method and system for optimizing high-speed train crew scheduling plans based on heuristic algorithms. The method includes: generating virtual routes with consistent origin and destination stations by pairing routes in the route set where the origin and destination stations are inconsistent; solving the problem using a heuristic algorithm to obtain a single-cycle route sequence covering all routes once; and generating a crew scheduling plan based on the single-cycle route sequence. This method, through the design of a specialized route preprocessing and matching mechanism, intelligently pairs outbound and return routes to form virtual routes, and combines feasible connection rules and connection time cost matrices to transform the scheduling problem into a single-cycle route sequence optimization problem for heuristic solution. This not only ensures the feasibility of the scheduling plan, but also improves overall operational efficiency by optimizing pairing and compressing non-duty time such as outbound stops.

The application relates to a substation inspection scheme planning method for an extreme load scene, which comprises the following steps: constructing a substation inspection model fusing a value-keeping scene; proposing a dynamic updating mechanism of an inspection path adapting to the change of the number of stations; establishing a time-cost collaborative planning model considering resource constraints to generate an optimal inspection scheme considering the inspection time length and fuel cost; defining work length, station inspection proportion, overtime intensity, work frequency and fatigue degree as work quantity evaluation indexes, constructing an inspection task allocation model, and optimizing and solving the substation inspection scheme with the most balanced work quantity allocation. The application constructs a multi-dimensional work quantity evaluation index system and an inspection task allocation model, realizes the balanced allocation of work quantities among various inspection teams, and provides a scientific decision basis for personnel scheduling in operation and maintenance management.

This invention discloses a low-disturbance-impact method for railway passenger service scheduling, comprising: generating several initial scheduling plans sequentially using a greedy algorithm constrained by scheduling rules; using these initial scheduling plans as the initial population for a particle swarm optimization algorithm; globally optimizing the initial scheduling plans with scheduling rule satisfaction and disturbance impact indicators as optimization objectives to obtain a baseline passenger service scheduling scheme; acquiring sudden impact events; performing semantic extraction and credibility calculation on the sudden impact events to obtain structured event objects, and converting them into constraint objects; extracting the set of affected resources and the set of affected task links from the constraint objects; determining the repair area based on the set of affected resources and the set of affected task links; using the baseline passenger service scheduling scheme as the initial value, performing a local update search based on task relationships within the repair area to generate candidate solutions in the domain; selecting the optimal feasible local solution with minimal disturbance to update the baseline passenger service scheduling scheme.