Abstract: A computer system for controlling operation of a vehicle travelling from a starting location to a target location includes a memory and a semiconductor-based processor forming one or more logic circuits configured to generate a travel itinerary by selecting different highway segments on a map for the vehicle to drive over at respective speeds from the starting location to the target location subject to an arrival time deadline for arriving at the target location. Each of the highway segments has a distance that can be driven at the respective speed in less than a continuous driving time limit. The computer system sends the travel itinerary to a vehicle operator to drive the vehicle over the different highway segments with instructions to make a stop at the end of each highway segment to stay below the continuous driving time limit.

Abstract: A framework to generate coupons is described herein. In accordance with one aspect of the framework, historical data is retrieved from the database and used to predict sales orders within a time period of a marketing campaign. One or more of the predicted sales orders are selected to maximize return-on-investment within one or more constraints. Coupons are generated based on the selected one or more predicted sales orders for distribution to customers. Results of the generated coupons may then he transmitted to one or more client devices.

Abstract: Described herein is a framework to facilitate fraud inspection. In accordance with one aspect of the framework, one or more fraud rules are generated based on the historical data by performing machine learning. The one or more fraud rules are applied to select records from input records for physical inspection. The selected records may then be transmitted to one or more output devices to initiate physical inspection for fraud.

Abstract: A method of manufacturing at least a first product and a second product with at least a first machine and a second machine at minimum cost in an environment in which a cost of energy used by the first machine and the second machine varies as a function of time may include generating multiple chromosomes, determining fitness scores of each of the chromosomes, randomly generating, with probabilities based on the fitness scores, new chromosomes, determining fitness scores of the new chromosomes, selecting one of the new chromosomes with an optimal fitness score, and manufacturing at least the first product and the second product with at least the first machine and the second machine according to a schedule based on the selected new chromosome.

Abstract: Software techniques are described for making predictions and associated decisions regarding resource optimization for production efficiency, and scheduling associated actions accordingly. For example, with respect to a large workforce of employees eligible for available or potential training programs, techniques are described for making eligibility decisions regarding the training programs based at least in part on predicting whether and when an employee or subset of employees will depart a company, as well as on predicting a future business demand for the skills conferred by the training program(s). Similarly, with respect to machine resources, techniques are described for predicting whether and when a machine will malfunction, as well as for predicting a future demand for the functions provided by the new or upgraded machine functionality.

Abstract: A non-transitory computer-readable storage medium may comprise instructions stored thereon for controlling operation of a vehicle travelling from a starting location to a target location. When executed by at least one processor, the instructions may be configured to cause a computing system to generate a travel itinerary for the vehicle to travel over different road segments at respective speeds between the starting location and the target location subject to an arrival time deadline for arriving at the target location, the different road segments being selected on a map to minimize a total fuel consumption of the vehicle in travelling from the starting location to the target location, and send the travel itinerary to a vehicle operator to operate the vehicle to travel over different road segments at respective speeds between the starting location and the target location.

Abstract: The present description provides data analysis for machine maintenance scheduling. For example, dynamic maintenance intervals are assigned for each machine being scheduled. Then, a system is provided for implementing a particle swarm optimization for finding an optimized maintenance schedule. In the optimization, an objective function is defined for maximizing production while minimizing relative maintenance cost.

Abstract: At least one human resource sufficient to fulfill a received production order may be retrieved from a human resources database in which individual human resources are characterized based on skill level, efficiency level, cost, and schedule availability. At least one machine resource sufficient to fulfill the production order may be retrieved from a machine resources database in which individual machine resources are characterized based on production level, machine availability, and cost. Sufficient inventory materials to fulfill the production order may be retrieved from an inventory database in which inventory materials are characterized based on inventory availability and cost.

Abstract: A schedule optimizer accesses a demand database storing a plurality of demands for delivery, and a vehicle database to obtain vehicle data for a plurality of delivery vehicles, the vehicle data included in a vehicle data structure. The schedule optimizer further includes a demand selection data structure handler configured to provide a plurality of demand selection data structures, each demand selection data structure configured to store an optimization variable and a vehicle list representing a subset of the plurality of vehicles. The schedule optimizer iteratively selects demands from the plurality of demands, based on a time-decaying likelihood of increasing the optimization variable, to thereby form a current route schedule for the current vehicle. The schedule optimizer determines an optimized route schedule, based on the current route schedule and at least one preceding route schedule of at least one preceding iteration.

Abstract: A multi-depot delivery schedule optimizer includes an iteration controller to initialize scheduling iterations for determining an optimized route schedule for a plurality of demands and a plurality of vehicles, in which at least one of the route schedules includes a first depot as a start location, at least one delivery location, and a second depot as an end location. The multi-depot delivery schedule optimizer further includes a particle handler to define a plurality of particles within a solution space of allowable route schedules, each particle representing an allowable route schedule and represented by a corresponding position within the solution space.

Abstract: A destination prediction generator accesses a passenger record database of travel records for individual passengers, and generates therefrom a classification model characterizing a probability that an individual passenger entering an origin station of a transit system will travel to a destination station of a plurality of destination stations. A passenger flow forecaster receives an ingress notification for an individual passenger at the origin station, and forecasts, based on attributes of the ingress notification as applied to the classification model, at least one predicted destination station of the plurality of destination stations. A view generator outputs, for the at least one predicted destination station, a predicted passenger flow for the at least one predicted destination that includes the individual passenger.

Abstract: A capacity verifier accesses an inventory database and a vehicle database, based on at least one of a plurality of perishable good orders to be delivered by a plurality of delivery vehicles to a plurality of delivery sites. A dispatch schedule generator generates an initial dispatch schedule in which each of the plurality of delivery vehicles is individually scheduled for delivery to at least one of the plurality of delivery sites to define a delivery assignment, each delivery assignment being subject to an associated expiration time window for the perishable good being delivered. A dispatch schedule optimizer executes an iterative updating of an initial dispatch schedule wherein, in each iteration, at least one delivery assignment is altered and a resulting dispatch schedule is evaluated relative to associated expiration time windows, until an optimized dispatch schedule is obtained.

Abstract: A system for forecast modeling includes at least one processor and at least one database that is operably coupled to the at least one processor. The database includes a time series data module that is configured to store time series data for a domain, an exogenous data module that is configured to store exogenous data associated with multiple exogenous factors and a feedback module that is configured to collect and store feedback data from multiple online users, where the feedback data is related to the exogenous data and the exogenous factors. The system includes a data pre-processor module that is configured to use the at least one processor to identify and select a portion of the exogenous factors using the feedback data collected from the online users for use in a forecast model in combination with the time series data for the domain.

Abstract: A classifier may be used to receive, via a website, user input associated with a product search of a user, and may be further used to identify a plurality of filters associated with the product search and predict a user-specific subset of the plurality of filters. Then, a filter manager may be used to provide a webpage of the website to the user, based on the user-specific filter subset.

Abstract: A system for self-adaptive user reading preference learning and screen layout optimization for multi-media information is disclosed. The system is particular useful for devices with small display form factors, such as mobile devices. Data flow diagram (DFD) technique is used to represent a model of the screen layout for visualization. The system processes input information, which includes user information, device information, context information, and the news. The delivery news is filtered in the news processing system and presented to a user based the user's interest, whereas device information and context information, are also factors that take effect in the modeling.

Abstract: A technology for multi-objective optimization is provided. In accordance with one aspect, historical data and real-time data of a network of interest are provided in an integrated database. User input containing a problem to be solved and user preference for solving the problem is received. An optimization function is identified for generating at least one solution to the problem. The optimization function is identified based on the user preference. In response to identifying a single objective optimization function, the optimization function is initiated from a single objective optimization function library. In response to identifying a multi-objective optimization function, the optimization function is initiated from a multi-objective optimization function library. The optimization function retrieves the historical and real-time data based on the user preference for solving the problem. A result comprising at least one solution to the problem is provided.

Abstract: A system and method for analyzing documents, such as posts, on-line reviews and comments from people based on topics of the documents, to determine general sentiment of users is disclosed. Topics from the documents and their corresponding sentiment polarities are extracted. The documents are regarded to be constituted by a series of topics. The sentiment for a topic is represented by a quadruple (k, so, h, i), where k is the topic, so is the sentiment opinion, h is the comment or post holder, and i is the document. A quintuple (k, sup, p, n, ne) is used to illustrate the topics and corresponding sentiments and is stored in S, where sup indicates the frequency of the topic, and p (positive), n (negative) and ne (neutral) are different types of opinions of the users. From the quintuple set S, every topic is related to three kinds of sentiment opinions (positive, negative, and neutral), enabling determination of popular topics in documents as well as the users' sentiment polarities.

Abstract: The disclosure relates to an evaluation system that is able to simulate a large number of passengers, metro stations and trains. The evaluation system runs the simulated metro system inside a computer and shows the statistical status of each passenger, each metro station and each train. The passenger simulation can take into account various factors, such as weather, day, time and special events. Both historical and real-time passenger flows are data used to simulate passengers. The metro station simulation generates stations that have specific maximum volume and specific maximum throughput. The train will be simulated according to a specific train schedule. Both the metro station simulation and train simulation may use both virtual and real-world data. Finally, an evaluator will show the statistical information for passengers, stations and trains.

Abstract: A recommendation system for generating location recommendations for drivers of public service vehicles is disclosed. The system segments a map of an area of interest into segments or regions and analyzes historical call data to estimate demand in the regions. The analysis also determines values of the calls in the regions. For example, the analysis estimates the probability of the calls and values of such calls in each region. The analysis may include time patterns to improve accuracy of the estimation. By using the results of the analysis along with current information, such as current location of a vehicle, current time, and real-time traffic information, a holding location recommendation is generated.

Abstract: Disclosed herein are technologies for facilitating placement of charging stations. In accordance with one aspect, sensor data of electric vehicles is received. A charging demand distribution over a set of locations is determined based on the sensor data. Candidate locations are selected from the set of locations based on the charging demand distribution. Placement of charging stations at one or more of the candidate locations is then optimized.