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A new approach for the optimal design of mixed refrigerant cycles is presented. It is based on mathematical programming and offers significant improvements in relation to previous approaches. It includes multistage refrigerant compression, full enforcement of the minimum temperature difference in heat exchangers, simultaneous optimization of variables, consideration of capital costs, and the use of stochastic optimization (genetic algorithm) to overcome local optima. The approach can be applied to either single mixed refrigerant cycles or to systems consisting of two of these in cascade. The effectiveness of the method is illustrated by revisiting previously published liquified natural gas case studies, for which better and feasible solutions are produced, and which prove the importance of considering multistage compression and capital costs during optimization. The application of genetic algorithms in the design of mixed refrigerant cycles permits a greater confidence in the optimality of the results.

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