A Discrete Choice Modeling Approach to Modular Systems Design
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
A Discrete Choice Modeling Approach to Modular Systems Design

Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.

Keywords: Constrained discrete combinatorial choice, modular systems design, optimization problem, PC configuration.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058115

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2023

References:


[1] P. T. Kidd. Agile Manufacturing: Forging New Frontiers, Addison Wesley, New York, 1994.
[2] J. K. Gershenson, G. J. Prasad. Modularity in product design for manufacturability. Int. J. of Agile Manufacturing, vol. 1, no 1, pp. 1-11, 1997.
[3] Tzu-Liang (Bill) Tseng, Chun-Che Huang. Design support systems: A case study of modular design of the set-top box from design knowledge externalization perspective, Decision Support Systems, vol. 44, no 4, pp. 909-924, 2008.
[4] J. T. Dorsey, T. J. Collins, W. R. Doggett, R. V. Moe. Framework for defining and assessing benefits of a modular assembly design approach for exploration systems. in Proc. Space Technology and Applications International Forum - STAIF 2006, vol. 813, pp. 969-981.
[5] A.K. Kamrani, E.A. Nasr. Collaborative Engineering. Springer, 2008, ch. 10.
[6] A. S├│bester, A. I.J. Forrester, D. J.J. Toal, E. Tresidder, S. Tucker, Engineering design applications of surrogate-assisted optimization techniques, Optimization and Engineering, DOI 10.1007/s11081-012- 9199-x, 2012.
[7] K. Fujita. Product variety optimization under modular architecture. Computer-Aided Design, vol. 34, no. 12, pp. 953-965, 2002.
[8] M. S. Levin. Combinatorial Optimization in System Configuration Design, Automation and Remote Control, vol. 70, no. 3, pp. 519-561, 2009.
[9] K. Fujita, H. Sakaguchi, S. Akagi. Product variety deployment and its optimization under modular architecture and module communalization. Proc. of the ASME Design Engineering Technical Conferences, 1999, Las Vegas, Nevada, DETC99/DFM-8923.
[10] Re-Designing The Computer: The Birth of the Modular Computer". Xi3 Corporation. http://xi3.com/white_paper.pdf.
[11] V. Tam, K. T. Ma. Using heuristic-based optimizers to handle the personal computer configuration problems, in Proc. 12th IEEE Int. Conf. on Tools with Artificial Intelligence, 2000, pp. 108-111.
[12] V. Tam, K. T. Ma. Optimizing personal computer configurations with heuristic-based search methods, Artificial Intelligence Review, vol. 17, no 2, pp. 129-140, 2002.
[13] L. Jae-Kyu, S. Sung-Hoon, K. Suhn-Baum. Configuration of personal computer by constraint and rule satisfaction problem approach. in Proc. First Asian Paciific DSI Conference, Hongkong, 1996, pp. 1-22.
[14] T. Soininen, I. Niemela, J. Tiihonen, R. Sulonen. Unified configuration knowledge representation using weight constraint rules, in Proc. ECAI- 2000 Workshop on Configuration, pp. 79-84, Berlin, 2000.
[15] J. McDermott. R1: A Rule-based Configurer of Computer Systems, Artificial Intelligence, vol. 19, no. 1, pp. 39-88, 1982.
[16] V. B. Kreng, Tseng-Pin Lee., Modular product design with grouping genetic algorithm - a case study. Computers & Industrial Engineering, vol. 46, no. 3, pp. 443-460, 2004.
[17] Lindo Systems, http://www.lindo.com.