Efficient Metaheuristic Algorithms for a Robust and Sustainable Water Supply and Wastewater Collection System

Abstract

An efficient design of a water supply and wastewater collection system is significantly important to tackle the natural uncertainty of this system and the sustainable development goals in developing countries like Iran. To address the natural uncertainty in the water supply and the challenge of global warming, this design must be robust and this motivates a robust optimization. To consider the sustainability criteria, this design should cover all economic, environmental and social impacts. Hence, this study develops innovative solutions based on recent and traditional metaheuristic algorithms for a robust and sustainable water supply and wastewater collection system. Red deer algorithm (RDA) and Keshtel algorithm (KA) as the recent algorithms, are employed. These recent algorithms are compared with the state-of-the-art methods like genetic algorithm (GA) and particle swarm optimization (PSO). An application of our model and algorithms, is tested on a case study in North Khorasan province. After performing some analyses on the performance of our algorithms and sensitivities on the model, a discussion is provided to conclude managerial insights and findings for practitioners in the applied system.