Resultados:
Ebrahimnejad, A., Tavana, M., & Vincent, C. (2022). Analytics under uncertainty: A novel method for solving linear programming problems with trapezoidal fuzzy variables. Soft Computing, 26(1), 327-347. https://doi.org/10.1007/s00500-021-06389-7 [Published: January (1st Quarter/Winter) 2022]
Kheirollahi, H., Hessari, P., Vincent, C., & Chawshini, R. (2018). An input relaxation model for evaluating congestion in fuzzy DEA. Croatian Operational Research Review, 8(2), 391-408. doi.org/10.17535/crorr.2017.0025 [Published: 2018]
Asthana, A. N. (2014). Profitability prediction in catlle ranches in Latin America: A Machine Learning Approach. Global Veterinaria, 13(4), 473-495. doi:10.5829/idosi.gv.2014.13.04.1179
Charles, V., Kumar, M., & Suggu, S. (2013). Chance constrained programming approach to QFD: An application to quality requirement planning of a B-School. Journal of ISPS, 13(1), 39-53. www.researchgate.net/publication/224969516…
Charles, V. (2011). Stochastic fractional programming approach to a mean and variance model of a transportation problem. Mathematical problem in engineering, 2011, 1-12. http://dx.doi.org/10.1155/2011/657608
Charles, V., Udhayakumar, A., & Uthariaraj, R. (2010). Stochastic simulation-based genetic algorithm for chance constrained fractional programming problem. International Journal of Operational Research, 9(1), 23-38. http://dx.doi.org/10.1504/IJOR.2010.034359