Robust and Stochastically Weighted Multiobjective Optimization Models and Reformulations

Published Online:https://doi.org/10.1287/opre.1120.1071

References

  • Abdelaziz FB, Aounib B, Fayedha RE. Multi-objective stochastic programming for portfolio selection. Eur. J. Oper. Res. (2007) 177(3):1811–1823CrossrefGoogle Scholar
  • Alba E, Dorronsoro B, Luna F, Nebro AJ, Bouvry P, Hogie L. A cellular multi-objective genetic algorithm for optimal broadcasting strategy in metropolitan manets. Comput. Comm. (2007) 30(4):685–697CrossrefGoogle Scholar
  • Amjady N, Aghaei J, Shayanfar H. Stochastic multiobjective market clearing of joint energy and reserves auctions ensuring power system security. IEEE Trans. Power Systems (2009) 24(4):1841–1854CrossrefGoogle Scholar
  • Aretoulis GN, Kalfakakou GP, Striagka FZ. Construction material supplier selection under multiple criteria. Oper. Res. (2010) 10(2):209–230Google Scholar
  • Ben-Tal A, Ghaoui LE, Nemirovski A. Robust Optimization (2009) (Princeton University Press, Princeton, NJ) CrossrefGoogle Scholar
  • Borcherding K, Eppel T, von Winterfeldt D. Comparison of weighting judgements in multiattribute utility measurement. Management Sci. (1991) 37(12):1603–1619LinkGoogle Scholar
  • Canfora G, Troiano L. A model for opinion agreement and confidence in multi-expert multi-criteria decision making. Mathware and Soft Comput. (2004) 11(2):67–82Google Scholar
  • Chen A, Kim J, Seungjae L, Youngchan K. Stochastic multi-objective models for network design problem. Expert Systems with Appl.: An Internat. J. (2010) 37(2):1608–1619CrossrefGoogle Scholar
  • Chew V. Confidence, prediction, and tolerance regions for the multivariate normal distribution. J. Amer. Statist. Assoc. (1966) 61(315):605–617CrossrefGoogle Scholar
  • Côtéa P, Parrotta L, Sabourinb R. Multi-objective optimization of an ecological assembly model. Ecological Informatics (2007) 2(1):23–31CrossrefGoogle Scholar
  • Cromvik C, Lindroth P, Patriksson M, Strömberg A-B. A new robustness index for multi-objective optimization based on a user perspective. (2011) . Technical report, Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, SwedenGoogle Scholar
  • Davis J. Group decision and social interactions: A theory of social decision schemes. Psych. Rev. (1973) 80(2):97–125CrossrefGoogle Scholar
  • Davis J. Group decision making and quantitative judgments: A consensus model. Understanding Group Behaviour Consensual Action by Small Groups (1996) 1(Lawrence Erlbaum, Mahwah, NJ) . Chap. 3Google Scholar
  • Deb K, Gupta H, Coello Coello C, Hernández Aguirre A, Zitzler E. Searching for robust Pareto-optimal solutions in multi-objective optimization. Evolutionary Multi-Criterion Optimization (2005) 3410(Springer, Berlin) 150–164Lecture Notes in Computer ScienceCrossrefGoogle Scholar
  • Delage E, Ye Y. Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. (2010) 58(3):595–612LinkGoogle Scholar
  • Dyer R, Forman E. Group decision support with the analytic hierarchy process. Decision Support Systems (1992) 8(2):99–124CrossrefGoogle Scholar
  • Edwards W. How to use multiattribute utility measurement for social decision making. IEEE Trans. Systems Man and Cybernetics (1977) 7(5):326–340CrossrefGoogle Scholar
  • Ehrgott M. Multicriteria Optimization (2005) (Springer, Berlin) Google Scholar
  • Gass S, Saaty T. The computational algorithm for the parametric objective function. Naval Res. Logist. Quart. (1955) 2(1--2):39–45CrossrefGoogle Scholar
  • Harsanyi J. Cardinal welfare, individualistic ethics, and interpersonal comparisons of utility. J. Political Econom. (1955) 63(4):309–321CrossrefGoogle Scholar
  • He S, Chen J, Xu W, Sun Y, Preetha T, Shen X. A stochastic multiobjective optimization framework for wireless sensor networks. EURASIP J. Wireless Comm. Networking (2010) . http://jwcn.eurasipjournals.com/content/2010/1/430615Google Scholar
  • Hoffman LA, Irwin SH, Toasa J. Forecast performance of futures price models for corn, soybeans, and wheat. (2007) Number 9889 in 2007 annual meeting(Agricultural & Applied Economics Association, Milwaukee, WI) Google Scholar
  • Hu J, Homem-de-Mello T, Mehrotra S. Risk adjusted budget allocation models with application in homeland security. IIE Trans. (2011) 43(12):819–839CrossrefGoogle Scholar
  • Kandil A, El-Rayes K, El-Anwar O. Optimization research: Enhancing the robustness of large-scale multiobjective optimization in construction. J. Construction Engrg. Management (2010) 136(1):17–25CrossrefGoogle Scholar
  • Kantanantha N, Serban N, Griffin P. Yield and price forecasting for stochastic crop decision planning. J. Agricultural, Biological, and Environ. Statist. (2010) 15(3):362–380CrossrefGoogle Scholar
  • Keeney R. A group preference axiomatization with cardinal utility. Management Sci. (1976) 23(2):140–145LinkGoogle Scholar
  • Keeney RL, Raiffa H. Decisions with Multiple Objectives: Preferences and Value Tradeoffs (1976) (John Wiley & Sons, New York) Google Scholar
  • Komiya H. Elementary proof for Sion's minimax theorem. Kodai Math. J. (1988) 11(1):5–7CrossrefGoogle Scholar
  • Korhonen P, Salo S, Steure R. A heuristic for estimating nadir criterion values in multiple objective linear programming. Oper. Res. (1997) 45(5):751–757LinkGoogle Scholar
  • Liu P, Pistikopoulos EN, Li Z. A multi-objective optimization approach to polygeneration energy systems design. AIChE J. (2010) 56(5):1218–1234CrossrefGoogle Scholar
  • Lounis Z, Vanier DJ. A multiobjective and stochastic system for building maintenance management. Comput.-Aided Civil and Infrastructure Engrg. (2000) 15(5):320–329CrossrefGoogle Scholar
  • Marcenaro-Gutierreza OD, Luqueb M, Ruizb F. An application of multiobjective programming to the study of workers' satisfaction in the Spanish labour market. Eur. J. Oper. Res. (2010) 203(2):430–443CrossrefGoogle Scholar
  • Matsatsinis NF, Samaras AP. MCDA and preference disaggregation in group decision support systems. Eur. J. Oper. Res. (2001) 130(2):414–429CrossrefGoogle Scholar
  • Mehrotra S, Kim K. Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights. Health Care Management Sci. (2011) 14(4):324–337CrossrefGoogle Scholar
  • Mehrotra S, Özevin G. Convergence of a weighted barrier decomposition algorithm for two-stage stochastic programming with discrete support. SIAM J. Optim. (2010) 20(5):2474–2486CrossrefGoogle Scholar
  • Miettinen KM. Nonlinear Multiobjective Optimization (1999) (Kluwer Academic Publishers, Norwell, MA) Google Scholar
  • Pöyhönen M, Hämäläinen RP. Theory and methodology on the convergence of multiattribute weighting methods. Eur. J. Oper. Res. (2001) 129(3):569–585CrossrefGoogle Scholar
  • Prato T, Herath G. Multiple-criteria decision analysis for integrated catchment management. Ecological Econom. (2007) 63(2--3):627–632CrossrefGoogle Scholar
  • Ramanathan R, Ganesh LS. Group preference aggregation methods employed in AHP: An evaluation and an intrinsic process for deriving members' weightages. Eur. J. Oper. Res. (1994) 79(2):249–265CrossrefGoogle Scholar
  • Reed MR, Riggins SK. Corn yield response: A micro-analysis. North Central J. Agricultural Econom. (1982) 4(2):91–94CrossrefGoogle Scholar
  • Rockafellar RT. Convex Analysis (1972) (Princeton University Press, Princeton, NJ) Google Scholar
  • Ruszczyński A, Shapiro A. Stochastic Programming (2003) (Elsevier Science Publishing, Amsterdam) Handbooks in Operations Research and Management ScienceCrossrefGoogle Scholar
  • Saaty TL. The Analytic Hierarchy Process (1980) (McGraw-Hill, New York) Google Scholar
  • Schoemaker PJH, Waid CC. An experimental comparison of different approaches to determining weights in additive utility models. Management Sci. (1982) 28(2):182–196LinkGoogle Scholar
  • Shapiro A, Ruszczyński A, Shapiro A. Monte Carlo sampling methods. Handbook of Stochastic Optimization (2003) (Elsevier Science Publishers B.V., Amsterdam) 353–425CrossrefGoogle Scholar
  • Sion M. On general minimax theorems. Pacific J. Math. (1958) 8(1):171–176CrossrefGoogle Scholar
  • Soares G, Adriano RLS, Maia C, Jaulin L, Vasconcelos JA. Robust multi-objective team22 problem: A case study of uncertainties in design optimization. IEEE Trans. Magnetics (2009) 45(3):1028–1031CrossrefGoogle Scholar
  • Stepanov A, Smith JM. Multi-objective evacuation routing in transportation networks. Eur. J. Oper. Res. (2009) 198(2):435–446CrossrefGoogle Scholar
  • Steuer R. Multiple Criteria Optimization: Theory, Computation, and Application (1986) (John Wiley & Sons, New York) Google Scholar
  • Thompson LM. Weather variability, climatic change, and grain production. Science (1975) 188(4188):535–541CrossrefGoogle Scholar
  • Tsiporkovaa VEB. Multi-step ranking of alternatives in a multi-criteria and multi-expert decision making environment. Inform. Sci. (2006) 176(18):2673–2697CrossrefGoogle Scholar
  • USDA Quick Stats 2.0. (2011) . National Agricultural Statistics Service, July 2011. http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.aspGoogle Scholar
  • Utomo C, Idrus A, Napiah M, Khamidi MF. Agreement options on multi criteria group decision and negotiation. Internat. J. Math. Statist. Sci. (2009) 1(1):9–13Google Scholar
  • von Winterfeldt D, Edwards W. Decision Analysis and Behavioral Research (1986) (Cambridge University Press, Cambridge, UK) Google Scholar
  • Weber M, Borcherding K. Behavioral influences on weight judgments in multiattribute decision making. Eur. J. Oper. Res. (1993) 67(1):1–12CrossrefGoogle Scholar
  • Yang K, Trewn J. Multivariate Statistical Methods in Quality Management (2004) (McGraw-Hill, New York) Google Scholar
  • Zadeh L. Optimality and non-scalar-valued performance criteria. IEEE Trans. Automatic Control (1963) 8(1):59–60CrossrefGoogle Scholar
  • Zhang Q, Maeda S, Kawachi T. Stochastic multiobjective optimization model for allocating irrigation water to paddy fields. Paddy and Water Environment (2007) 5(2):93–99CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.