Amazon Technologies, Inc.

Jingqiao Zhang

Girish S Lakshman

Michael Mahesh Bhaskaran

Lin Wan

Jeffrey B Maurer

Pradeep Desai

Ali Sadighian

Deepak Bhatia

Richa Agarwal

Zhihao Cen

Jingchen Wu

Karthik Balasubramanian

Marc A Onetto

Techniques for computing a feature based on variables may be provided. For example, historical realizations associated with a first variable may be accessed. The first variable may be associated with an item. Realizations of the first variable may be based on one or more factors associated with the item. Historical realization of a second variable associated with the item may also be accessed. The historical realizations of the first and second variables may be analyzed to generate an expected realization of the first variable as a function of the second variable. The feature may be computed based on the generated function.

Efficiently computing a feature based on a plurality of variables

Various embodiments of a system and method for constraint-based reduction of a solution space for vehicle routing are described. Embodiments may include a system configured to identify sets of redundant routes within a solution space. For each given set of redundant routes, the system may utilize one or more constraints associated with conveying shipments on routes of the given set in order to eliminate one or more routes of that set from consideration. For each of multiple routes of the given set that have not been eliminated from consideration, the system may determine a respective cost associated with utilizing that route. The system may also, in response to determining that the cost associated with a particular route that has not been eliminated from consideration is less than the cost associated with other routes that have not been eliminated from consideration, add the particular route to a reduced solution space.

System and method for constraint-based reduction of a solution space for vehicle routing

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Redmond, WA, United States of America

Jingqiao Zhang