APPROXIMATE SOLUTIONS OF STOCHASTIC LINEAR PROGRAMS WITH ESTIMATED OBJECTIVE FUNCTION: AN APPLICATION OF RE-SAMPLING METHODS

Carlos N. BOUZA-HERRERA[1]

Sira M. ALLENDE-ALONSO1

Daniel C. CHEN[2]

§    ABSTRACT:  In this paper we consider the effect of using an approximation to the upper bound of the Minimax optimal solution in Stochastic Linear Programming.  It can be computed accepting the normality or by using a re-sampling method.  Simulated Annealing is introduced for looking for the second stage solution.  Least Absolute Deviation is proposed as an alternative to Least Squares for computing the initial solution.  The proposals are compared through Monte Carlo Simulation experiments.

§    KEYWORDS: Bootstrap; Jacknife; L1 norm; stochastic programming, environmental impact of solid waste compost.

 



[1] Facultad de Matemática y Computación, Universidad de La Habana, San Lazaro y L. Vedado. CP 10400, La Habana, Cuba. E-mail: bouza@matcom.uh.cu

[2] Smith and King College Lenin Sarajani #129, Calcutta India. E-mail: Dchen19@gmail.com