Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design

A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. Pareto solutions single-mixed refrigerant (SMR) propane-precooled mixed (C3MR) compared to determine suitability each terms energy area. Kriging models ɛ-constraint methodology used sequentially provide simple surrogate subproblems, whose minimizers promising feasible non-dominated original problem. ɛ-constrained subproblems solved GAMS CONOPT. Fronts achieved with dominate results from NSGA-II, a well-established meta-heuristics optimization. objective functions go as low 1045 980.3 kJ/kg-LNG specific UA values 212.2 266.9 kJ/(°C kg-LNG) for SMR C3MR, respectively. trade-off that present minimum sum relative analyzed well dominance C3MR over at conversely