International Business Machines Corporation

John Nathan Rachlin

Seshashayee Sankarshana Murthy

Frederick Yung-Fung Wu

Rama Kalyani Tirumala Akkiraju

Brenda Lynn Dietrich

Rama K Akkiraju

Martin Clarence Sturzenbecker

Robin Lougee-Heimer

Raymond T Henry

Robert Mack Fuhrer

Pinar Keskinocak

Prediction methods that anticipate the outcome of a detailed optimization step are used in lieu of or in conjunction with actual optimization to improve response time and reduce required computational resources for optimization problems having a hierarchical structure. Decomposition of the optimization problem into sub-problems and sub-sub-problems is, itself, an optimization process which is iteratively performed while preferably guided by prediction of the quality of solutions to the problems into which the &ldquo;master&rdquo; optimization problem may be decomposed. Prediction also reduces the requirements for computational resources and allows more decompositions to be examined within the available time in order to arrive at a more nearly optimal decomposition as well as a more nearly optimal solution. Prediction is selectively used when it is determined that such a benefit is probable.

Optimization prediction for industrial processes

Customer-service tasks are performed in a noninvasive manner by relying on automatic methods for (a) capturing the state of the operating domain and (b) automatically communicating this state as well as a description of the circumstances that lead to activation of the process to a remote service machine via an electronic network. Network-based customer-service for software support includes an automatic mechanism which initiates the product support process. This automatic mechanism may optionally be augmented by a manual mechanism for initiating the support process. The process captures the operating environment in sufficient detail so as to enable its re-creation in part or in whole on a separate machine. Archived data is transmitted to an off-site storage device, and when this data is received, notification is transmitted to customer-support personnel. The operating environment is re-created, and the customer-support person investigates the problem by executing the software product in the re-created environment.

Non-invasive networked-based customer support

A method for effecting computer implemented decision support. The method can improve on a candidate solution by allowing problem solving methods to cooperate towards the creation of a more desirable solution. The method can realize an enhanced understanding of tradeoffs inherent in competing objectives, and can incorporate factors or special considerations not easily specified, by enabling the decision maker to actively participate in the creation of a more desirable solution.

Multi-objective decision-support methodology

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Tarrytown, NY, United States of America

John Nathan Rachlin