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A linear approximation method for solving a special class of the chance constrained programming problem

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  • Zare M., Yahia
  • Daneshmand, Ahmad

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  • Zare M., Yahia & Daneshmand, Ahmad, 1995. "A linear approximation method for solving a special class of the chance constrained programming problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 213-225, January.
  • Handle: RePEc:eee:ejores:v:80:y:1995:i:1:p:213-225
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    References listed on IDEAS

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    1. Seppala, Yrjo & Orpana, Tuomo, 1984. "Experimental study on the efficiency and accuracy of a chance-constrained programming algorithm," European Journal of Operational Research, Elsevier, vol. 16(3), pages 345-357, June.
    2. C. van de Panne & W. Popp, 1963. "Minimum-Cost Cattle Feed Under Probabilistic Protein Constraints," Management Science, INFORMS, vol. 9(3), pages 405-430, April.
    3. Fredrick S. Hillier, 1967. "Chance-Constrained Programming with 0-1 or Bounded Continuous Decision Variables," Management Science, INFORMS, vol. 14(1), pages 34-57, September.
    4. Yrjö Seppälä, 1971. "Constructing Sets of Uniformly Tighter Linear Approximations for a Chance Constraint," Management Science, INFORMS, vol. 17(11), pages 736-749, July.
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    Cited by:

    1. Tan, Q. & Huang, G.H. & Cai, Y.P., 2011. "Radial interval chance-constrained programming for agricultural non-point source water pollution control under uncertainty," Agricultural Water Management, Elsevier, vol. 98(10), pages 1595-1606, August.
    2. Anetta Caplanova & Keith Willett, 2019. "Emission Discharge Permit Trading and Persistant Air Pollutants (A Common Pool Market Application with Health Risk Specifications)," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 19-38, February.
    3. 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.
    4. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
    5. Poojari, Chandra A. & Varghese, Boby, 2008. "Genetic Algorithm based technique for solving Chance Constrained Problems," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1128-1154, March.
    6. Zhengping Liu & Wang Zhang & Hongxian Liu & Guohe Huang & Jiliang Zhen & Xin Qi, 2019. "Characterization of Renewable Energy Utilization Mode for Air-Environmental Quality Improvement through an Inexact Factorial Optimization Approach," Sustainability, MDPI, Open Access Journal, vol. 11(8), pages 1-19, April.
    7. Sun, Wei & Huang, Guo H. & Lv, Ying & Li, Gongchen, 2013. "Inexact joint-probabilistic chance-constrained programming with left-hand-side randomness: An application to solid waste management," European Journal of Operational Research, Elsevier, vol. 228(1), pages 217-225.
    8. Wu, C.B. & Huang, G.H. & Li, W. & Xie, Y.L. & Xu, Y., 2015. "Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1244-1254.
    9. Kampas, Athanasios & White, Ben, 2003. "Probabilistic programming for nitrate pollution control: Comparing different probabilistic constraint approximations," European Journal of Operational Research, Elsevier, vol. 147(1), pages 217-228, May.

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