Abstract: In one aspect, a computerized method for using machine learning methods for modeling for time in traffic for a vehicle on a delivery route includes the step of collecting a set of traffic feature values from a database. The method includes the step of normalizing the set of traffic feature values. The method includes the step of providing a machine learning model. The method includes the step of inputting the set of normalized traffic features into the machine learning model. The method includes the step of training the machine learning model with the set of normalized traffic features. The method includes the step of determining a target time for the vehicle on the delivery route.

Abstract: A computerized system for global positioning service (GPS) location polling based on user locomotive activity comprising: a mobile device comprising a GPS receiver, a display, a central processing unit (CPU) and a wireless communication transceiver coupled to the GPS receiver, an accelerometer sensor, and a gyroscope sensor, wherein the CPU is programmed to: estimate a position of the GPS receiver based on a location data, detect a motion state of a user of the mobile device based on either an accelerometer sensor data or a gyroscope sensor data, wherein the motion state of the user is set to a not moving state, a walking state, or a driving state.

Abstract: In one aspect, a method comprises identifying a set of main components of an address that have a highest importance for a specified geography are identified. The method comprises providing a geocoding database comprising a dataset of geocoded addresses of a geocoder. The method comprises receiving a set of responses from the geocoding database, wherein each response comprises a geocoded addresses of the geocoding database. The method comprises breaking each response into a set of components. The method comprises, based on the set of components, matching the address and each response in the set of components; based on the match, calculating a string similarity score and a component match score of each response between the address and each response. The method comprises sorting the responses based on the string similarity score of each response and the component match score of each response. The method comprises selecting a first response of the set of responses after sorting as the best response.

Abstract: A computerized method for optimizing a geocoding process by automatically determining points of interest (POIs) within a locality includes the step of providing, from a first database comprising a first set of POIs, wherein the first set of POIs are obtained from a government agency. The method includes the step of geocoding all the POIs in the first database. The method includes the step of providing a second database of a second set of POIs that exist only in local context but not part of first database maintained by the government agency. The method includes the step of geocoding all the POIs in the second database. The second database is generated by the step of using n-gram analysis to discover a second set of POIs in a geographic region of the locality of the first database.

Abstract: A computerized method for optimizing a geocoding process by automatically determining points of interest (POIs) within a locality includes the step of providing, from a first database comprising a first set of POIs, wherein the first set of POIs are obtained from a government agency. The method includes the step of geocoding all the POIs in the first database. The method includes the step of providing a second database of a second set of POIs that exist only in local context but not part of first database maintained by the government agency. The method includes the step of geocoding all the POIs in the second database. The second database is generated by the step of using n-gram analysis to discover a second set of POIs in a geographic region of the locality of the first database.

Abstract: A computerized method for implementing an optimal supply chain configuration includes the step of implementing an optimal supply chain configuration for a business. The method includes the step of modelling costs for minimization in an optimal supply chain configuration. The method includes the step of modelling constraints in an optimal supply chain configuration. The method includes the step of, based on the modelled cost for minimization and the modelled constraints, optimizing a supply chain for the business.

Abstract: In one aspect, a computerized method of automated solution for periodic journey planning comprising includes the step of creating a set of salesbeats using a set of outlet data and a set of customer level data. The method includes the step of allocating each of the salesbeats to one or more sales executives. A salesbeat includes a plan that defines who to visit; when to visit; an identity of a sales executives to send and a day level route plan made for field sales/marketing personnel to make visits to a number of stores at a predefined frequency. The method includes the step of allocating the sales executives are allocated to a specified set of days. The method includes the step of implements sequencing of outlets within the salesbeats established using a capacitated vehicle routing problem (CVRP) algorithm such that a distance traveled and a time window of the salesbeat is optimized for the sales executives.

Abstract: In one aspect, a computerized method for using machine learning methods for modeling for time in traffic for a vehicle on a delivery route includes the step of collecting a set of traffic feature values from a database. The method includes the step of normalizing the set of traffic feature values. The method includes the step of providing a machine learning model. The method includes the step of inputting the set of normalized traffic features into the machine learning model. The method includes the step of training the machine learning model with the set of normalized traffic features. The method includes the step of determining a target time for the vehicle on the delivery route.