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Trade-off studies

Trade-off studies

Tradeoff studies are broadly recognized and mandated as the method for simultaneously considering multiple alternatives with many criteria, and as such are recommended in the Capability Maturity Model Integration (CMMI) Decision Analysis and Resolution (DAR) process. Tradeoff studies can be studied extensively through mathematics, or, in contrast, by value engineering. Tradeoff studies, which involve human numerical judgment, calibration, and data updating, are often approached with under confidence by analysts and are often distrusted by decision makers. The decision-making fields of Judgment and Decision Making, Cognitive Science and Experimental Economics have built up a large body of research on human biases and errors in considering numerical and criteria-based choices. Relationships between experiments in these fields and the elements of tradeoff studies show that tradeoff studies are susceptible to human mental mistakes RIMES focuses on development of objective methods and techniques to eliminate the presence, or ameliorate the effects of mental mistakes on tradeoff studies.
  • Complementary Decompositions for Systems within Systems, Hugo Almaraz, Ricardo Pineda and Eric D. Smith, Complementary Decompositions for Systems within Systems, Live Virtual Constructive (LVC) Conference, International Test & Evaluation Association (ITEA), El Paso, TX, 2011.

  • Clarity, Variety, Allocation, Synergy and Emergence in the Formulation of Tradeoff Studies, Eric D. Smith and Ricardo Pineda, Clarity, Variety, Allocation, Synergy and Emergence in the Formulation of Tradeoff Studies, Conference on Systems Engineering Research (CSER), Stevens Institute of Technology and the University of Southern California, Hoboken, NJ, 2010.

  • Sensitivity Analysis: A Powerful System Validation Technique, Eric D. Smith, Ferenc Szidarovszky, William J. Karnavas, and Terry Bahill, The Open Cybernetics & Systemics Journal, Bentham Open, Sensitivity Analysis: A Powerful System Validation Technique, 2008, Vol. 2, 39-56.

  • Ameliorating Mistakes in Tradeoff Studies, Eric D. Smith, Young Jun Son, Massimo Piattelli-Palmarini and A. Terry Bahill, Systems Engineering, 10(3), 222-240, 2007.

  • Cognitive Biases Affecting the Acceptance of Tradeoff Studies, Eric D. Smith, Massimo Piattelli-Palmarini, and A. Terry Bahill, in Decision Modeling and Behavior in Uncertain and Complex Environments, J. C. Smith and T. Kugler editors, Springer, Cambridge, MA, 2007.

  • Tradeoff Studies and Cognitive Biases, Eric D. Smith, A. Terry Bahill, Proceedings of the International Council on Systems and Industrial, Manufacturing & Systems Engineering (INCOSE) 16th International Symposium, 2006, Orlando, FL.

  • Attribute Substitution in Systems Engineering, Eric D. Smith, A. Terry Bahill, Proceedings of the 2007 Industrial, Manufacturing & Systems Engineering Research Conference, G. Bayraksan, W. Lin, Y. Son, and R. Wysk, eds.

  • Taboada, H. & Coit, D. (2006). Data Mining Techniques to Facilitate the Analysis of the Pareto-Optimal Set for Multiple Objective Problems. In Proceedings of the Industrial, Manufacturing & Systems Engineering Research Conference (IERC), Orlando, Florida, May 2006.

  • Taboada, H. & Coit, D. (2008). Multiple Objective Scheduling Problems: Determination of Pruned Pareto Sets. IIE Transactions, 40(5):552-564.

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