Amazon Technologies, Inc.

I2 Technologies Us, Inc.

Southwest Airlines Co.

David John Michael

Timothy Lee Jacobs

Lingan Satkunanathan

Mehdi Sheikhzadeh

Manoj Abraham

Russell John Allgor

Eric Johnson Schaffer

Narayan Venkatasubramanyan

Hoda Parvin

Ozlem Bilginer

Na An

Timothy Bill

Nilay Noyan Bulbul

Xiaofeng Wei

Chieh Hsien Tiao

Mark Mcfarland

Devices and techniques are generally described for on-time performance impact evaluation. In some examples, first flight plan data that includes a plurality of scheduled air-based routes may be determined. A first route of the plurality of scheduled air-based routes may be selected for a first package. First scan data related to the first package may be received. A first slack time associated with the first package on a first flight of the first route may be determined based at least in part on the first scan data. The first package being assigned to the first route may be evaluated based at least in part on the first slack time.

On-time performance impact evaluation tool

Features related to systems and methods for network planning based on optimization modeling of equipment and item transmissions. The network planning may include a model to plan for transmission of items over a network to maximize overall efficiencies over alternative transmission modes. The model may produce a network plan that schedules transmissions, determines the number and types of equipment needed to support the transmissions, assigns equipment to specific locations, and optimally routes items throughout the network.

Network planning and optimization

A schedule for a network of transportation resources is produced by iteratively generating sets of variables for each market pair using an objective function and based on at least an identified range of permissible departure or arrival times for each market pair and spacing parameters. Each variable represents a different set of possible departure or arrival times for a particular market pair. The proposed schedule is built based on the generated sets of variables for each market pair and a set of constraints.

Schedule optimization using market modeling

Generating a supply chain plan includes accessing data describing a supply chain network having buffers. Each buffer is operable to store items and is associated with a corresponding time variable. The supply chain network is constrained by a constraint. A linear programming problem is generated for the supply chain network. The linear programming problem is approximated by discretizing the time variables of the buffers to yield discretized time variables and by relaxing the constraint to yield a relaxed constraint. An optimized supply chain plan is calculated for the approximated linear programming problem. The optimized supply chain plan describes a quantity of items at each buffer for at least one time value of the corresponding time variable. The optimized supply chain plan is adjusted to satisfy the constraint.

Generating a supply chain plan

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Dallas, TX, United States of America

David John Michael