Many Objective Visual Analytics: In Search of Search-as-a-Service

[1]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[2]  Patrick M. Reed,et al.  The Value of Online Adaptive Search: A Performance Comparison of NSGAII, epsilon-NSGAII and epsilonMOEA , 2005, EMO.

[3]  Lucas Bradstreet,et al.  A Fast Way of Calculating Exact Hypervolumes , 2012, IEEE Transactions on Evolutionary Computation.

[4]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[5]  Patrick M. Reed,et al.  Many-Objective Evolutionary Optimisation and Visual Analytics for Product Family Design , 2011, Multi-objective Evolutionary Optimisation for Product Design and Manufacturing.

[6]  Zahed Siddique,et al.  Product Platform and Product Family Design , 2006 .

[7]  Christopher A. Mattson,et al.  Usage scenarios for design space exploration with a dynamic multiobjective optimization formulation , 2013 .

[8]  H. Kita,et al.  Failure of Pareto-based MOEAs: does non-dominated really mean near to optimal? , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[9]  Donald A. Norman.  New views of information processing: implications for intelligent decision support systems , 1986 .

[10]  Olivier Teytaud,et al.  On the Hardness of Offline Multi-objective Optimization , 2007, Evolutionary Computation.

[11]  Bernard Yannou,et al.  Set-based design by simulation of usage scenario coverage , 2013 .

[12]  Patrick M. Reed,et al.  Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework , 2013, Evolutionary Computation.

[13]  Kalyanmoy Deb,et al.  Higher-level innovization: A case study from Friction Stir Welding process optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[14]  Raphael T. Haftka,et al.  Structural optimization complexity: what has Moore’s law done for us? , 2004 .

[15]  Patrick M. Reed,et al.  Many objective visual analytics: rethinking the design of complex engineered systems , 2013 .

[16]  Kalyanmoy Deb,et al.  Evaluating the -Domination Based Multi-Objective Evolutionary Algorithm for a Quick Computation of Pareto-Optimal Solutions , 2005, Evolutionary Computation.

[17]  William A. Crossley,et al.  Exploring Different Problem Formulations to Evaluate Environmental Impacts of Aviation , 2012 .

[18]  Patrick M. Reed,et al.  Diagnostic Analysis of Metamodels’ Multivariate Dependencies and Their Impacts in Many-Objective Design Optimization , 2013, DAC 2013.

[19]  C. Coello,et al.  Multiobjective optimization using a micro-genetic algorithm , 2001 .

[20]  Soon-Thiam Khu,et al.  An Investigation on Preference Order Ranking Scheme for Multiobjective Evolutionary Optimization , 2007, IEEE Transactions on Evolutionary Computation.

[21]  Shigeru Obayashi,et al.  Multi-Objective Design Exploration and Its Application to Regional-Jet Wing Design , 2007 .

[22]  R. Hogarth.  Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. , 1981 .

[23]  Alexis Tsoukiàs,et al.  From decision theory to decision aiding methodology , 2008, Eur. J. Oper. Res..

[24]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[25]  Joseph R. Kasprzyk,et al.  Evolutionary multiobjective optimization in water resources: The past, present, and future , 2012 .

[26]  Christopher A. Mattson,et al.  Divergent exploration in design with a dynamic multiobjective optimization formulation , 2013 .

[27]  Jouni Lampinen,et al.  GDE3: the third evolution step of generalized differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.

[28]  Shapour Azarm,et al.  Metrics for Quality Assessment of a Multiobjective Design Optimization Solution Set , 2001 .

[29]  Timothy W. Simpson,et al.  Introduction of a product family penalty function using physical programming , 2000 .

[30]  Patrick M. Reed,et al.  Diagnostic Assessment of Search Controls and Failure Modes in Many-Objective Evolutionary Optimization , 2012, Evolutionary Computation.