Chance Constrained Programming with Exponential Input Coefficients | ||||
| The Egyptian Statistical Journal | ||||
| Article 3, Volume 61, Issue 1, June 2017, Page 41-57 PDF (5.06 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2017.270058 | ||||
 View on SCiNiTO | ||||
| Abstract | ||||
| In this paper, we consider chance constrained programming (CCP) technique when at least two of the LHS input coefficients are random with two-parameter exponential distribution. Two approaches are introduced to transform CCP into deterministic: (i) approach 1 assumes independence between exponential input coefficients and (ii)approach 2 assumes that random input coefficients are dependent with correlation coefficient ρ. Approach 1 for independence is an extension of Biswal's approach deals with m independent two – parameter exponential input coefficients instead of single-parameter ones. Approach 2 of dependence uses Downton bivariate exponential (DBE) distribution under two cases; the first introduced case assumes that dependent input coefficients have single-parameter exponential marginals and the second introduced case is an extension of DBE distribution for two-parameter exponentials. It was shown that the equivalent deterministic transformation of the extension of approach 2 is a generalization of both approach 1 for m=2 when ρ=0 and first case of approach 2 for single parameter exponential marginal when the second parameter is zero | ||||
| Keywords | ||||
| Bessel function - Biswal's approach - chance Constrained Programming Downton bivariate exponential distribution - input coefficients; non-linear Programming - probabilistic Programming - stochastic Programming two – parameter exponential distribution | ||||
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