Proxy Approach to Multi-attribute Decision Making
Department of Engineering-Economic Systems, Stanford University., 1977 - Decision making - 226 pages
In many decision problems, the possible outcomes have several important dimensions of value. To identify the optimal alternative, the decision analyst must assess the decision maker's preferences over these multi-attribute outcomes. Two rival procedures for solving multi-attribute preference problems currently exist. These two procedures, global preference modeling and local preference modeling, each have advantages and disadvantages. This dissertation combines these two rival procedures in a new approach to multi-attribute decision making. This new combined method, called the proxy approach, uses the advantages of one technique to overcome the disadvantages of the other.
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THE PROXY ITERATION ALGORITHM
THE NEW ALGORITHM VERSUS THE
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additional allocation Appendix approximation algorithm assess tradeoffs assessment error assumptions attributes Boyd's algorithm Cobb-Douglass Cobb-Douglass proxy convex programming curriculum decision analysis decision maker's preferences decision problem deterministic preference axioms deterministic preference function direction of improvement dk+1 error by tradeoff feasible direction Figure global convergence global preference modeling global procedure grade gradient Grenke guarantee Hessian matrix indifference curve ITERATION IMPROVED OBJECTIVE LAGRANGE MULTIPLIER language arts line search linear approximation linear proxy lottery modified Frank-Wolfe algorithm multi-attribute decision multi-attribute problem multi-attribute utility theory nonlinear normatively motivated numeraire optimal solution parameters point consistency test PREDICTED IMPROVEMENT price variable proxy approach proxy function proxy iteration algorithm rate of convergence rates of substitution Research restrictive shadow price skew social studies spacer step successive point consistency sum-of-exponentials proxy sum-of-powers symmetric teach technique tradeoff assessments trial points trial sequence trial solution true objective true preference function upper school V(xk vector xk+1