The development of Genetic Algorithm for minimizing a wastewater

This paper aims to develop genetic algorithm (GA) for solving the wastewater minimisation. The optimisation model is formulated as linear programming (LP) and non-linear programming (NLP) for single and multiple contaminants system. Especially GA that is the core of this paper is an algorithm based on the principal of evolution and heredity. The GA included mass balances for every contaminant as well as for every operation units. Therefore The GA was composed of solving both for single contaminant and multiple contaminants with problems which was formulated by a MILP model. So we formulated a MILP model with several problems. And the GA was coded with C language. The GA will reduce the amount of wastewater and the water-usage as well as the cost of piping and the operation cost of network, when we use this program to solve several problems, the result is better than results of other software, and other tools. In some cases, the configuration of water network is simpler than former methods. Especially for the multiple contaminants, the amount of freshwater is better in some problems. This paper aims to develop genetic algorithm (GA) for solving the wastewater minimization. The result of this program is adapted in real industry and can save operation cost from 10% to 20%.