IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v126y2000i3p651-661.html
   My bibliography  Save this article

A sampling-based method for generating nondominated solutions in stochastic MOMP problems

Author

Listed:
  • Ringuest, Jeffrey L.
  • Graves, Samuel B.

Abstract

No abstract is available for this item.

Suggested Citation

  • Ringuest, Jeffrey L. & Graves, Samuel B., 2000. "A sampling-based method for generating nondominated solutions in stochastic MOMP problems," European Journal of Operational Research, Elsevier, vol. 126(3), pages 651-661, November.
    • Handle: RePEc:eee:ejores:v:126:y:2000:i:3:p:651-661
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(99)00318-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. G. Klein & H. Moskowitz & A. Ravindran, 1990. "Interactive Multiobjective Optimization Under Uncertainty," Management Science, INFORMS, vol. 36(1), pages 58-75, January.
    2. Santhanam, Radhika & Kyparisis, George J., 1996. "A decision model for interdependent information system project selection," European Journal of Operational Research, Elsevier, vol. 89(2), pages 380-399, March.
    3. Ralph E. Steuer & Minghe Sun, 1995. "The Parameter Space Investigation Method of Multiple Objective Nonlinear Programming: A Computational Investigation," Operations Research, INFORMS, vol. 43(4), pages 641-648, August.
    4. Mareschal, Bertrand, 1986. "Stochastic multicriteria decision making and uncertainty," European Journal of Operational Research, Elsevier, vol. 26(1), pages 58-64, July.
    5. Weber, R. & Werners, B. & Zimmermann, H. -J., 1990. "Planning models for research and development," European Journal of Operational Research, Elsevier, vol. 48(2), pages 175-188, September.
    6. Peter H. Farquhar, 1984. "State of the Art---Utility Assessment Methods," Management Science, INFORMS, vol. 30(11), pages 1283-1300, November.
    7. Pekka Korhonen & Jyrki Wallenius & Stanley Zionts, 1984. "Solving the Discrete Multiple Criteria Problem using Convex Cones," Management Science, INFORMS, vol. 30(11), pages 1336-1345, November.
    8. Teghem, J. & Dufrane, D. & Thauvoye, M. & Kunsch, P., 1986. "Strange: An interactive method for multi-objective linear programming under uncertainty," European Journal of Operational Research, Elsevier, vol. 26(1), pages 65-82, July.
    9. A. Charnes & W. W. Cooper, 1963. "Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints," Operations Research, INFORMS, vol. 11(1), pages 18-39, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    2. Medaglia, Andres L. & Graves, Samuel B. & Ringuest, Jeffrey L., 2007. "A multiobjective evolutionary approach for linearly constrained project selection under uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 869-894, June.
    3. Hassanzadeh, Farhad & Nemati, Hamid & Sun, Minghe, 2014. "Robust optimization for interactive multiobjective programming with imprecise information applied to R&D project portfolio selection," European Journal of Operational Research, Elsevier, vol. 238(1), pages 41-53.
    4. Farhad Hassanzadeh & Hamid Nemati & Minghe Sun, 2013. "Robust Optimization for Interactive Multiobjective Programming with Imprecise Information Applied to R&D Project Portfolio Selection," Working Papers 0194mss, College of Business, University of Texas at San Antonio.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Urli, Bruno & Nadeau, Raymond, 2004. "PROMISE/scenarios: An interactive method for multiobjective stochastic linear programming under partial uncertainty," European Journal of Operational Research, Elsevier, vol. 155(2), pages 361-372, June.
    2. Shin-Liang Chan & Wann-Ming Wey & Pin-Huai Chang, 2014. "Establishing Disaster Resilience Indicators for Tan-sui River Basin in Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(1), pages 387-418, January.
    3. Fatima Bellahcene, 2019. "Decision maker's preferences modeling for multiple objective stochastic linear programming problems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(3), pages 5-16.
    4. Medaglia, Andres L. & Graves, Samuel B. & Ringuest, Jeffrey L., 2007. "A multiobjective evolutionary approach for linearly constrained project selection under uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 869-894, June.
    5. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    6. Panos Xidonas & Haris Doukas & George Mavrotas & Olena Pechak, 2016. "Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model," Annals of Operations Research, Springer, vol. 247(2), pages 395-413, December.
    7. Thomas L. Saaty, 2013. "The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach," Operations Research, INFORMS, vol. 61(5), pages 1101-1118, October.
    8. Hang Li & Zhe Zhang & Xianggen Yin & Buhan Zhang, 2020. "Preventive Security-Constrained Optimal Power Flow with Probabilistic Guarantees," Energies, MDPI, vol. 13(9), pages 1-13, May.
    9. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    10. Tavana, Madjid & Khosrojerdi, Ghasem & Mina, Hassan & Rahman, Amirah, 2019. "A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process," Evaluation and Program Planning, Elsevier, vol. 77(C).
    11. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    12. Bogdan Rębiasz, 2016. "New method of selecting efficient project portfolios in the presence of hybrid uncertainty," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 26(4), pages 65-90.
    13. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    14. Abdellaoui, Mohammed & Bleichrodt, Han, 2007. "Eliciting Gul's theory of disappointment aversion by the tradeoff method," Journal of Economic Psychology, Elsevier, vol. 28(6), pages 631-645, December.
    15. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    16. Nowak, Maciej, 2007. "Aspiration level approach in stochastic MCDM problems," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1626-1640, March.
    17. Christian Meier & Dennis Kundisch & Jochen Willeke, 2017. "Is it Worth the Effort?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(2), pages 81-95, April.
    18. Ming Ding & Jehoshua Eliashberg, 2002. "Structuring the New Product Development Pipeline," Management Science, INFORMS, vol. 48(3), pages 343-363, March.
    19. R. Caballero & E. Cerda & M. Muñoz & L. Rey, 2002. "Analysis and comparisons of some solution concepts for stochastic programming problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(1), pages 101-123, June.
    20. Yael Grushka-Cockayne & Bert De Reyck & Zeger Degraeve, 2008. "An Integrated Decision-Making Approach for Improving European Air Traffic Management," Management Science, INFORMS, vol. 54(8), pages 1395-1409, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:126:y:2000:i:3:p:651-661. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.