A domestic wastewater treatment train consists of a series of unit operations of various types, i.e., for preliminary, primary, secondary, tertiary, and advanced treatment and residual management. Many options are available for each type of unit operations. The challenge is to select treatment trains for which the extent and reliability of treatment is high, while the capital, operation and maintenance (O&M) costs of the treatment and land area requirement is low. This proposition has been

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... lated as a multi-objective optimization problem. The problem was solved using a genetic algorithm to determine the pareto-optimal ('no worse than each other) set of solutions under three conditions, i.e., when the environmental cost (E) was not constrained, and for E<75, and E<50. The results indicated that the optimal solution set contained more solutions with elaborate treatment trains when E was constrained. Furthermore, the correctness of the algorithm was demonstrated by showing that the set of optimal solutions remain approximately the same irrespective of the variations in the initial population size chosen for genetic operations.