Methods and program products for optimizing problem clustering

Data processing: artificial intelligence – Machine learning – Genetic algorithm and genetic programming system

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

10774676

ABSTRACT:
Exemplary embodiments of the present invention are directed to methods and program products for optimizing clustering of a design structure matrix. An embodiment of the present invention includes the steps of using a genetic operator to achieve an optimal clustering of a design structure matrix model. Other exemplary embodiments of the invention leverage the optimal clustering by applying a genetic operator on a module-specific basis.

REFERENCES:
patent: 5930762 (1999-07-01), Masch
patent: 5940816 (1999-08-01), Fuhrer et al.
patent: 5963902 (1999-10-01), Wang
patent: 6490572 (2002-12-01), Akkiraju et al.
patent: 6615205 (2003-09-01), Cereghini et al.
patent: 6768973 (2004-07-01), Patel
patent: 7047169 (2006-05-01), Pelikan et al.
patent: 2003/0055614 (2003-03-01), Pelikan et al.
patent: 2005/0256684 (2005-11-01), Jin et al.
Optimization on Design Structure Matrix Method and its Application for Shipbuilding Planning Linyi Deng; Yan Lin; Chaoguang Jin; Ming Chen; Qianwen You; Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on vol. 2, Jun. 21-23, 2006 pp. 7395-7399 Digital Object Identifier 10.1109/WCICA.2006.1714523.
A simulation-based optimization framework for product development cycle time reduction Abdelsalam, H.M.E.; Bao, H.P.; Engineering Management, IEEE Transactions on vol. 53, Issue 1, Feb. 2006 pp. 69-85 Digital Object Identifier 10.1109/TEM.2005.861805.
Enterprise Knowledge Based Database for New Product Development process K. M. Tham; S. A. Sharif; B. Kayis; Management of Innovation and Technology, 2006 IEEE International Conference on vol. 1, Jun. 2006 pp. 427-431 Digital Object Identifier 10.1109/ICMIT.2006.262198.
Application of DSM-based process reengineering in multidisciplinary cooperative design Lu-ning Xu; He-ming Zhang; Wen-sheng Xu; Yong-kang Zhang; Computer Supported Cooperative Work in Design, 2005. Proceedings of the Ninth International Conference on vol. 2, May 24-26, 2005 pp. 961-965 vol. 2.
Product development process intelligent analysis and improvement Yao Yong; Xiong Guangleng; Fan Wenhui; Fan Xiaodong; Networking, Sensing and Control, 2004 IEEE International Conference on vol. 1, Mar. 21-23, 2004 pp. 412-417 vol. 1 Digital Object Identifier 10.1109/ICNSC.2004.1297473.
Mapping product innovation profile to product development activities—the I-DSM tool Bilalis, N.; Maravelakis, E.; Antoniadis, A.; Moustakis, V.; Engineering Management Conference, 2004. Proceedings. 2004 IEEE International vol. 3, Oct. 18-21, 2004 pp. 1018-1022 vol. 3 Digital Object Identifier 10.1109/IEMC.2004.1408845.
Managing unmanned flight projects using methods in complex product development Mohan, S.N.; Aerospace Conference Proceedings, 2002. IEEE vol. 7, Mar. 9-16, 2002 pp. 7-3473-7-3488 vol. 7 Digital Object Identifier 10.1109/AERO.2002.1035324.
Product development process capture and display using Web-based technologies Sabbaghian, N.; Eppinger, S.; Murman, E.; Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on vol. 3, Oct. 11-14, 1998 pp. 2664-2669 vol. 3 Digital Object Identifier 10.1109/ICSMC.1998.725062.
Engineering design management: an information structure approach Yassine, A.; Innovation in Technology Management—The Key to Global Leadership. PICMET '97: Portland International Conference on Management and Technology Jul. 27-31, 1997 p. 483 Digital Object Identifier 10.1109/PICMET.1997.653479.
An analytical method based on design structure matrix for modular identification Xiaogang, X.; Chao, L.; Jian, Y.; Yahua, C.; Computer-Aided Industrial Design and Conceptual Design, 2006. CAIDCD '06. 7th International Conference on Nov. 2006 pp. 1-4 Digital Object Identifier 10.1109/CAIDCD.2006.329358.
A New Task Assignment Approach in Concurrent Engineering Bo Yang; Xiangbo Ze; Luning Liu; Computer Supported Cooperative Work in Design, 10th International Conference on May 2006 pp. 1-6 Digital Object Identifier 10.1109/CSCWD.2006.253010.
An Study on Information Security Optimization Based on MFDSM Jun-Jie Lv; Wan-Hua Qiu; Yuan-Zhuo Wang; Na Zou; Machine Learning and Cybernetics, 2006 International Conference on Aug. 2006 pp. 2732-2736 Digital Object Identifier 10.1109/ICMLC.2006.258989.
Goldberg, D. E., (1993a). “Making genetic algorithms fly: A lesson from the Wright brothers.”Advanced Technology for Developers, 2, 1-8.
Ohsawa, Y., Benson, N. E., & Yachida, M., (1998) “KeyGraph: Automatic indexing by co-occurrence graph based on building construction metaphor.” InProceedings of Advances in Digital Libraries, pp. 12-18.
Takama, Y., & Hirota, K. (2000). “Discovery of topic distribution through WWW information retrieval process.”Proceedings of 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation, 1644-1647.
Bingham, E., Kaban, A., & Girolami, M., (2003). “Topic identification in dynamical text by complexity pursuit.”Neural Processing Letters, 17(1), 69-83.
Graetz, K., Barlow, C., Proulx, N., & Pape, L. (1997). “Facilitating idea generation in computer-based teleconferences,”Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work(GROUP '97), 317-324.
Santanem, E., Briggs, R., & de Vreede, G. J., (2000). “The Cognitive Network Model of Creativity: a New Casual Model for Creativity and a New Brainstorming Technique,”Proceedings of the 33rdAnnual Hawaii International Conference on System Sciences, 2004.
Santanem, E., Briggs, R., & de Vreede, G.-J., (2002). “Toward an Understanding of Creative Solution Generation,”Proceedings of the 35thAnnual Hawaii International Conference on System Sciences, 2899-2908.
Goldberg, D.E., Sastry K., and Ohsawa Y., “Discovering Deep Building Blocks for Competent Genetic Algorithms Using Chance Discovery via KeyGraphs,” (2003) pp. 1-23.
Goldberg, D. E., (1993b). “A Wright-brothers theory of genetic algorithms flight.”Systems, Control, and Information, 37(8), 450-458.
Kosorukoff, A., & Goldberg, D. E. (2002). “Evolutionary computation as a form of organization.”Proceedings of the Genetic and Evolutionary Computation Conference(GECCO 2002), 965-972.
Takagi, H. (2001). “Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation.”Proceedings of the IEEE, 89(9), 1275-1296.
Welge, M. E., Auvil, L., Shirk, A., Bushell, C., Bajcsy, P., Cai, D., Redman, T., Clutter, D., Aydt, R., & Tcheng, D., (2003).Data to Knowledge(D2K) (Automated Learning Group Technical Report). Urbana, IL: National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign.
Altus, S., Kroo, I., & Gage, P., AGenetic Algorithm for Scheduling and Decomposition of Multidisciplinary Design Problems, ASME Journal of Mechanical Design, vol. 118, Dec. 1996.
Harik, G.,Linkage learning via probabilistic modeling in the ECGA. IlliGAL TR-99010, University of Illinois at Urbana-Champaign, Urbana, IL, 1999.
Lutz, R.,Recovering High-Level Structure of Software Systems Using a Minimum Description Length Principle, R.F.E. Proceedings of the 13thIrish International Conference, Artificial Intelligence and Cognitive Science (AICS 2002), Sep. 2002.
Munemoto, M., & Goldberg, D.E.,Liknage Identification by Non-monotonocity Detection for Overlapping Functions. IlliGAL Report No. 99005, Genetic and Evolutionary Computation Conference (GECCO-99), vol. 1, 1999.
Pelikan, M., Goldberg, D.E., & Cantú-Paz, E.,BOA: The Bayesian optimization algorithm. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99), vol. 1, pp. 525-532. Also IlliGAL TR-99003, University of Illinois at Urbana-Champaign, 1999.
Rogers, J. L.,DeMAID/GA User's Guide-Design Manager's Aid for Intelligent Decomposition With a Genetic Algorithm, NASA TM-110241, Apr. 1996.
Salman, A., Mehrota, K., & Mohan, C.,Linkage Crossover for Genetic Algorithms, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Methods and program products for optimizing problem clustering does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Methods and program products for optimizing problem clustering, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods and program products for optimizing problem clustering will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3898614

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.