Maintenance Policies Comparison by Multi-Objective Optimization Using Genetic Algorithm for Liquefied Natural Gas Pipeline

نویسندگان

  • Sanling Song
  • David W. Coit
  • Nida Chatwattanasiri
چکیده

Reliability analysis for liquefied natural gas (LNG) pipeline network brings researchers huge challenges because the system experience multiple dependent competing failure processes. Based on system reliability R(t) and time to failure distribution f(t) analyzed from system failure modes and mechanisms, we can generate LNG pipeline life data. Different maintenance policies can be considered as alternatives. Improving system performance and saving maintenance cost are two aspects of the trade-off that we want to consider. Multiobjective optimization is done by genetic algorithm considering uncertain LNG pipeline life data. Probabilistic Pareto frontier rather than deterministic Pareto front for candidate maintenance policies are given. Final decision is made based on optimization results comparison for two maintenance policies. Especially Pareto Uncertainty Index (PUI) model is used to distinguish two policies if they are overlapping around the area that users are

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تاریخ انتشار 2016