Computer aided optimization of natural gas pipe networks using genetic algorithm

This study is concerned to determine the optimum pipe size for networks used in natural gas applications. The genetic algorithm has been used in optimizing network parameters. The topology of the network is predefined. The study deals with the discrete nature of decision variables, namely, pipe diameters, as they are usually available in market in standard sizes. Hard constraints and soft constraints are considered. An imposed penalty factor is introduced to allow solutions that violate soft constraints to remain in the population during the solution progress guiding the algorithm convergence to a minimum network cost. In a case study, engineers with average experience of 6 years in the design office of a gas company performed the design of a gas network problem using their experience and judgment. The adopted method by engineers depends on a trial and error, time consuming, procedure. Their results are compared with the results obtained from the developed genetic algorithm optimization technique. The developed optimization technique has provided a distinctive reduction in the total cost of pipe networks over the existing heuristic approach which is based on human experience and judgment. A saving up to 12.1% has been achieved using the present analysis, in the special case studied.

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