Stochastic linear programming
Comparison of defuzzification methods for fuzzy stochastic linear programming
... Fuzzy linear programming has been studied extensively by numerous researchers, however, only few studies on fuzzy stochastic linear programming can be found up to date (Giri, Maiti and ...
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Fuzzy Stochastic Linear Programming Problems With Uncertainty Probability Distribution
... Since linear programming is one of the maximum significant tool, but one of the most important applicable tool operational research in the real life worldoptimizationproblems (Lilien, 1987; Meyer ...
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Chance Constrained Approaches for Multiobjective Stochastic Linear Programming Problems
... Multiple objective stochastic linear programming is a relevant topic. As a matter of fact, many practical problems rang- ing from portfolio selection to water resource management may be cast into ...
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Some Explicit Results for the Distribution Problem of Stochastic Linear Programming
... a stochastic linear programming problem, where either the objective function coefficients or the right hand side coefficients are continuous random vectors with known probability ...of ...
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Interactive Fuzzy Decision Making for Hierarchical Multiobjective Stochastic Linear Programming Problems
... tive stochastic linear programming problems (HMOP) where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common ...
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A Stochastic Linear Programming Model for Asset Liability Management: The Case of an Indian Insurance Company
... A stochastic linear programming model (on the lines of Pirbhai, 2004) maximises the net worth of the firm and also takes care of the ...of stochastic linear programming being ...
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Stochastic linear programming and
... are stochastic. One approach to solving stochastic linear programs is to take particu- lar values for the stochastic variables and solve the resulting deterministic ...use linear ...
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Multiobjective Stochastic Linear Programming: An Overview
... Received June 15, 2011; revised July 10, 2011; accepted July 29, 2011 Abstract Many Optimization problems in engineering and economics involve the challenging task of pondering both conflicting goals and random data. In ...
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Satisficing solutions for multiobjective stochastic linear programming problems
... Mathematical characterizations of these solution concepts have been obtained for the case of normal, exponential, chi-squared and gamma distributions. Extension to the case of fuzzy random variables has also been carried ...
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Calibrated American option pricing by stochastic linear programming
... a stochastic problem using the math- ematical technique of conjugate duality or alternatively Lagrange duality ...the linear programming problems for the buyer’s and the seller’s prices, but in the ...
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Software tools for Stochastic Programming: A Stochastic Programming Integrated Environment. (SPInE)
... OSL Stochastic Extension (King 1994) is an optimisation library which provides a set of routines for the manipulation and solution of multistage Stochastic Programming problems presented in SMPS ...
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On Stability in Multiobjective Integer Linear Programming: A Stochastic Approach
... A parametric study has been carried out on the problem under consideration, where some basic stability notions have been defined and characterized for the formulated prob[r] ...
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Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization
... About the Authors Masatoshi Sakawa joined the Integrated Modeling Environment in April 2009. His re- search and teaching activities are in the area of systems engineering, especially mathe- matical optimization, ...
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A possibility programming approach for stochastic fuzzy multiobjective linear fractional programs
... In this paper, a suggested stochastic fuzzy multiobjective linear fractional program is presented, in which the fuzzy coefficients and scalars in the linear fraction[r] ...
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Development of new scenario decomposition techniques for linear and nonlinear stochastic programming
... of stochastic mixed integer programming (MIP) problems, Løkketangen and Woodruff [42] introduced a new convergence crite- rion: integer ...from linear to nonlinear subproblems on the number of itera- ...
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Linear Programming Introduction to Linear Programming Problems
... Method of solving linear programming problem is referred as Corner Point Method. The method comprises of the following steps: 1. Find the feasible region of the linear programming problem and ...
Quasi-Monte Carlo methods for linear two-stage stochastic programming problems
... two-stage linear stochastic programming ...piecewise linear-quadratic, but do not belong to the function spaces considered for QMC error ...
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Linear Programming. Non-Lecture J: Linear Programming
... West. Linear programming was rediscovered and applied to shipping problems in the early 1940s by Tjalling ...solve linear programming problems, called the simplex method, was published by ...
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Linear Programming
... 7.115 Susanna Nanna is the production manager for a furniture manufacturing company. The company produces tables (X) and chairs (Y). Each table generates a profit of $80 and requires 3 hours of assembly time and 4 hours ...
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Linear Programming
... Optimal (feasible) solution: Any point in the feasible region that gives the optimal value (maximum or minimum) of the objective function is called an optimal solution. Now, we see that every point in the feasible region ...
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