. Using Random Dynamic Programming in Production Planning with Application in the midland Refineries Company

Abstract

This research deals with Building A probabilistic Linear programming model representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution . The Built programme is transformed in to deterministic one and then solved by using Dynamic Programming (Backward procedure) To find the Optimal values of Decision variables and Optimal value of Objective Function . All the results are explained in tables, we work on using Dynamic programming according to the Rule of Richard Bellman for Optimality,which depend on sub divide the Big problem ,in to This research deals with Building A probabilistic Linear programming model representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution . The Built programme is transformed in to deterministic one and then solved by using Dynamic Programming (Backward procedure) To find the Optimal values of Decision variables and Optimal value of Objective Function . All the results are explained in tables, we work on using Dynamic programming according to the Rule of Richard Bellman for Optimality,which depend on sub divide the Big problem ,in to sub problems Optimal Solutions each have,then this Solutions are Optimize to reach the final Optimal Solution. Optimal Solutions each have,then this Solutions are Optimize to reach the final Optimal Solution.