International Business Machines Corporation

Sachin Sethiya

Arun Hampapur

Xuan Liu

Ajay Ashok Deshpande

Saurabh Gupta

Ali Koc

Brian Leo Quanz

Christopher Scott Milite

Yingjie Li

Chek Keong Tan

Dahai Xing

Xiaobo Zheng

Ding Ding Lin

Pradyumnha Gopalkrishna Kowlani

Steve Igrejas

Vadiraja S Ramamurthy

Michael Yesudas

Sanjay E Cheeran

A predictive engine on a computer environment comprising a shared pool of configurable computing resources is executed to perform a predictive analysis on data pipelined into the computer environment, the data received from a plurality of sources and in a plurality of different formats, the predictive engine generating a network level cost information based on the predictive analysis on a dynamic and continuous basis. Asynchronous communication comprising the network level cost information from the predictive engine is received and a set of candidate nodes for order fulfillment is generated based on the network level cost information and a defined distance between the set of candidate nodes and a target destination. An optimization engine on the computer environment is invoked that filters the set of candidate nodes. A number of fulfillment nodes that meet one or more of a constraint and preconfigured rule is output.

Order sourcing with asynchronous communication and using optimization for large sourcing networks

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Billerica, MA, United States of America

Sachin Sethiya