Abstract: An embodiment discloses a sensor arrangement comprising disc shaped structure with a plurality of magnetic elements which are at least provided on end faces of the disc shaped structure. The sensor arrangement includes a hollow disc structure, the hollow disc structure comprising two end faces, wherein each of the two end faces of the second structure comprises a plurality of teeth spaced apart from each other, the teeth on the two end faces are arranged in opposing positions. Teeth on a respective same end face of the hollow disc structure are spaced from each other. The disc shaped structure is rotatable with respect to the hollow disc structure. A magnetic field sensor is provided to sense a magnetic field generated by the plurality magnetic elements.

Abstract: An embodiment discloses a sensor arrangement comprising disc shaped structure with a plurality of magnetic elements which are at least provided on end faces of the disc shaped structure. The sensor arrangement includes a hollow disc structure, the hollow disc structure comprising two end faces, wherein each of the two end faces of the second structure comprises a plurality of teeth spaced apart from each other, the teeth on the two end faces are arranged in opposing positions. Teeth on a respective same end face of the hollow disc structure are spaced from each other. The disc shaped structure is rotatable with respect to the hollow disc structure. A magnetic field sensor is provided to sense a magnetic field generated by the plurality magnetic elements.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinatorial optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinatorial optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinatorial optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinatorial optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinational optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.