Design and optimization of the cost of a crude oil pipeline by Genetic Algorithm technique

Abstract

The optimization of the design of a pipeline involves a number of variables, which include pipe diameter, pressure, temperature, line length, required inlet and delivery pressures and delivery quantity. The cost elements include the physical parameters: Cost of material, pipe, cost of fuel and energy, cost of construction, cost of operation, (fuel maintenance; utilization), total life cycle cost, etc. Each of these parameters influences the overall construction and operating cost in some degree and the selection of one or more will determine the economics of the construction and operation of the system. This is as true for the design of a system from a clean sheet of paper (grass roots) as it is for the development and upgrading of an existing system, the only real difference between these two examples is the extent to which some of the variables are already fixed. The program we shall use for optimization is the Genetic Algorithm Technique. Genetic Algorithm (GA) is a powerful technique for solving optimization problems in hydraulic engineering. It is a method for solving both constrained and unconstrained optimization problems based on a natural selection process that mimics biological evolution. GA uses the main three operations, the selection, crossover and mutation to produce new generations from the old ones.