Randomized Algorithms for Lexicographic Inference

Consumers generally do not know about, much less evaluate, the hundreds or thousands of product variations available to them in a category. In many situations, including online shopping, they use p...

[1]  Rajeev Motwani,et al.  Randomized Algorithms , 1995, SIGA.

[2]  Gerhard Reinelt,et al.  A Cutting Plane Algorithm for the Linear Ordering Problem , 1984, Oper. Res..

[3]  U. Hoffrage,et al.  Fast, frugal, and fit: Simple heuristics for paired comparison , 2002 .

[4]  Fred W. Glover,et al.  An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem , 2001, J. Glob. Optim..

[5]  Patricia Rose Gomes de Melo Viol Martins,et al.  MATHEMATICS WITHOUT NUMBERS: AN INTRODUCTION TO THE STUDY OF LOGIC , 2015 .

[6]  M. F. Luce,et al.  Constructive Consumer Choice Processes , 1998 .

[7]  D. Bridges.  Numerical representation of intransitive preferences on a countable set , 1983 .

[8]  John W. Payne,et al.  Contingent decision behavior. , 1982 .

[9]  Young-Soo Myung,et al.  A cutting plane algorithm for computing k , 2004, Eur. J. Oper. Res..

[10]  Rafael Martí,et al.  Variable neighborhood search for the linear ordering problem , 2006, Comput. Oper. Res..

[11]  A. Tversky,et al.  Contingent weighting in judgment and choice , 1988 .

[12]  G. Debreu.  Mathematical Economics: Representation of a preference ordering by a numerical function , 1983 .

[13]  Michael Schmitt,et al.  On the Complexity of Learning Lexicographic Strategies , 2006, J. Mach. Learn. Res..

[14]  Peter C. Fishburn,et al.  LEXICOGRAPHIC ORDERS, UTILITIES AND DECISION RULES: A SURVEY , 1974 .

[15]  Ulrich Hoffrage,et al.  Why does one-reason decision making work? A case study in ecological rationality , 1999 .

[16]  John Liechty,et al.  Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis , 2005 .

[17]  Irène Charon,et al.  An updated survey on the linear ordering problem for weighted or unweighted tournaments , 2010, Ann. Oper. Res..

[18]  Dimitris Bertsimas,et al.  Robust Product Line Design , 2017, Oper. Res..

[19]  Jorge Nocedal,et al.  Representations of quasi-Newton matrices and their use in limited memory methods , 1994, Math. Program..

[20]  Mia Hubert,et al.  Deterministic algorithms for MCD and LTS , 2011 .

[21]  Robert M. Freund,et al.  Optimizing Product Line Designs: Efficient Methods and Comparisons , 2008, Manag. Sci..

[22]  Jerry A. Hausman,et al.  Assessing the potential demand for electric cars , 1981 .

[23]  M. F. Luce,et al.  The Rationalizing Effects of Cognitive Load on Emotion-Based Trade-off Avoidance , 2004 .

[24]  Peter P. Wakker,et al.  Continuity of preference relations for separable topologies , 1988 .

[25]  Robert S. Billings,et al.  The effects of response mode and importance on decision-making strategies: Judgment versus choice , 1988 .

[26]  A. Bröder.  Assessing the empirical validity of the "take-the-best" heuristic as a model of human probabilistic inference. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[27]  I. Pinelis.  EXACT UPPER AND LOWER BOUNDS ON THE DIFFERENCE BETWEEN THE ARITHMETIC AND GEOMETRIC MEANS , 2015, Bulletin of the Australian Mathematical Society.

[28]  A. Bröder,et al.  Take the best versus simultaneous feature matching: probabilistic inferences from memory and effects of representation format. , 2003, Journal of experimental psychology. General.

[29]  T. Stützle,et al.  The Linear Ordering Problem: Instances, Search Space Analysis and Algorithms , 2004 .

[30]  David P. Williamson,et al.  Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems , 2007, WAOA.

[31]  Rafael Martí,et al.  Intensification and diversification with elite tabu search solutions for the linear ordering problem , 1999, Comput. Oper. Res..

[32]  Ely Dahan,et al.  Greedoid-Based Noncompensatory Inference , 2007 .

[33]  R. Kohli,et al.  Representation and Inference of Lexicographic Preference Models and Their Variants , 2007 .

[34]  G. Gigerenzer,et al.  Probabilistic mental models: a Brunswikian theory of confidence. , 1991, Psychological review.

[35]  P. Slovic.  Choice Between Equally Valued Alternatives. , 1975 .

[36]  David P. Williamson,et al.  Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.

[37]  Paul E. Green,et al.  Models and Heuristics for Product Line Selection , 1985 .

[38]  A. Tversky.  Choice by elimination , 1972 .

[39]  J. S. Hunter,et al.  Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building. , 1979 .

[40]  Warren H. Hausman,et al.  Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis.: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis. , 2000 .

[41]  Ramesh Krishnamurti,et al.  A Heuristic Approach to Product Design , 1987 .

[42]  Irène Charon,et al.  A survey on the linear ordering problem for weighted or unweighted tournaments , 2007, 4OR.

[43]  John R. Hauser,et al.  Fast Polyhedral Adaptive Conjoint Estimation , 2002 .

[44]  Vicki Knoblauch,et al.  Lexicographic orders and preference representation , 2000 .

[45]  Anja Dieckmann,et al.  Compensatory versus noncompensatory models for predicting consumer preferences , 2009, Judgment and Decision Making.

[46]  M. Trick,et al.  Voting schemes for which it can be difficult to tell who won the election , 1989 .

[47]  Rajeev Kohli,et al.  Error Theory for Elimination by Aspects , 2015, Oper. Res..

[48]  Radford M. Neal.  Regression and Classification Using Gaussian Process Priors , 2009 .

[49]  A. Chateauneuf.  Continuous representation of a preference relation on a connected topological space , 1987 .

[50]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[51]  Dimitris Bertsimas,et al.  Exact First-Choice Product Line Optimization , 2017, Oper. Res..

[52]  Eric J. Johnson,et al.  Cognitive processes in preference reversals , 1989 .

[53]  Andrew Gelman,et al.  The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo , 2011, J. Mach. Learn. Res..