According to one aspect, a method for improved kitchen production is provided, the method comprising: receiving a request for one or more order items to be prepared in a kitchen, each of the one or more order items comprising: a recipe requiring: one or more resources for preparation, one or more processes for preparation, and an estimated preparation time, and a requested pickup time; retrieving a kitchen production capacity comprising a plurality of resources of the kitchen and a plurality of processes of the kitchen; projecting kitchen availability comprising: resource availability at a timeframe, process availability at the predetermined timeframe, current order items being prepared in the kitchen, and order items awaiting preparation in the kitchen; assessing the kitchen production capacity and the kitchen availability in view of the recipes of the one or more order items; and scheduling, based on the comparing, production the one or more order items.

An approach for predicting team dynamics based on changing circumstances. The approach retrieves profiles associated with a group of first team members of a project team. The approach selects a virtual reality (VR) scenario to interact with the group of first team members. The approach executes the VR scenario based on the profiles. The approach receives VR input from an interacting team member interacting with the VR scenario. The approach predicts responses of the group of first team members to the VR input. The approach analyzes the responses and provides the interacting team member a ranked list of scenario outcomes.

An information processing system includes a processor configured to cancel a first reservation of a place made by a first person for a time window in a case where a predetermined condition is met, and in a case where the first reservation has been cancelled, transmit information indicating that the place has become available to a second person who made a second reservation of the place for a time window different from the time window of the first reservation.

There is provided an information processing apparatus for efficiently processing various products. The information processing apparatus includes a determiner that receives signals from sensors respectively provided in a plurality of machine tools, determines operation statuses of the plurality of machine tools, and derives a plurality of usable machine tools, a receiver that receives product specifying data for specifying a product to be manufactured, a decider that decides, based on the product specifying data, a necessary machine tool required to process the product, and a presenter that searches for the necessary machine tool from the plurality of usable machine tools, and presents information concerning a use machine tool as a search result.

Example implementations described herein are directed to a system for manufacturing dispatching using reinforcement learning and transfer learning. The systems and methods described herein can be deployed in factories for manufacturing dispatching for reducing job-due related costs. In particular, example implementations described herein can be used to reduce massive data collection and reduce model training time, which can eventually improve dispatching efficiency and reduce factory cost.

Methods and systems for controlling production resources in a supply chain are described. The system automatically generates predicted supply chain operational metrics across a nodes of a supply chain. The system automatically infers causal factors that impact the predicted supply chain operational metrics. The causal factors include a change to a utilization of the production resource. The system communicates a user interface including production runs being scheduled on the production resource including a user interface element representing the scheduling of the production run associated with a value at risk. The system receives input causing a change to the utilization of the production resource. The change to the utilization of the production resource impacts the predicted supply chain operational metrics including the value at risk associated with the scheduling of the production run.

A method of coordinating a fleet of vehicles includes receiving a first preconditioning characteristic of a first battery from a first vehicle of the fleet of vehicles. The method further includes receiving a second preconditioning characteristic of a second battery from a second vehicle of the fleet of vehicles. The method further includes comparing the first preconditioning characteristic and the second preconditioning characteristic to determine a preconditioning ranking for the first vehicle and the second vehicle. The method further includes determining a queue of the first and second vehicles for a charging station using the preconditioning ranking of the first and second vehicles.

Prospective fault adaptation for project management includes generating a project in a project management system according to a timeline of different overlapping tasks and interdependent, a cost to completion and a count of human resources required to complete the tasks at or below the cost to completion. An indication of a prospective fault condition is received in connection with a task in the project. The prospective fault is then quantified and an adjustment computed to the timeline, cost to completion, count of human resources or scope. The adjustment is compared to a threshold value indicative of an acceptable project outcome. Finally, a visualization of the project is generated in the project management system including the flag and an alert representative of the comparison.

The present disclosure relates to the technical field of automated warehousing, and relates to an inventory scheduling method and device and a non-transitory computer readable storage medium. The method of the present disclosure includes: obtaining an order to be picked, the order to be picked comprising a kind(s) of goods to be picked; determining order processing capability information of each of a plurality of picking workstations, according to at least one of position distribution information of a rack(s) storing at least one kind of the goods to be picked relative to each of the picking workstations, position distribution information of an available transfer machine(s) relative to each of the picking workstations, or load information of each of the picking workstation; and allocating the order to be picked to one of the picking workstations according to the order processing capability information of each of the picking workstations.

An optimization apparatus for repeatedly obtaining a constraint violating solution, a constraint satisfying solution, and an approximate solution in a resource-constrained project scheduling problem performs setting an end time of a target optimization period at a point between a first finish time equal to a finish time of a latest version of the constraint violating solution and a second finish time equal to a finish time of a latest version of the constraint satisfying solution, followed by obtaining the approximate solution using a metaheuristic algorithm, making a determination as to whether the approximate solution violates constraint or satisfy the constraint, and performing, based on the determination, updating the first finish time with a finish time of the approximate solution when the approximate solution violates the constraint, and updating the second finish time with a finish time of the approximate solution when the approximate solution satisfies the constraint.