This paper describes the development of an adaptive locally constrained genetic algorithm (ALCO-GA) and its application to the problem of least cost water distribution network design. Genetic algorithms have been used widely for the optimisation of both theoretical and real-world nonlinear optimisation problems, including water system design and maintenance problems. In this work we propose a heuristic-based approach to the mutation of chromosomes with the algorithm employing an adaptive mutation operator which utilises hydraulic head information and an elementary heuristic to increase the efficiency of the algorithm's search into the feasible solution space. In almost all test instances ALCO-GA displays faster convergence and reaches the feasible solution space faster than the standard genetic algorithm. ALCO-GA also achieves high optimality when compared to solutions from the literature and often obtains better solutions than the standard genetic algorithm.
There`s a common economic paradox about the price tag on drinking water and value. Our current economic climate places prices on things predicated on scarcity and value. Water pricing is now more widespread, with the dual goal of expanding supply and encouraging more responsible use. So long as water remained abundant, the cheapness of drinking water is not likely to change. However, the price of water has entered into serious questioning.
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