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.
The customerSteel industry plants all over the world have multiple processes, most of them emitting CO and CO2 in very high concentrations (tens of %). CO is used as a combustible due to its high calorific value. It is stored in a huge tank before it is used by the power plant next door. CO in such high concentration is explosive in presence of a few molecules of oxygen. Therefore, continuous monitoring of the O2 concentration in the duct carrying the gas to the tank is a key and a safety issue.So far the measureme...
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