Many studies use genetic algorithms to model water distribution network and they give some interesting results. Recent studies propose a multi-objective model of the problem. But one of the drawbacks of genetic algorithm both mono and multi-objective is the extensive use of the evaluation process. In water systems design, the evaluation of the quality of a water distribution network requires a ...

Abstract This work introduces a new bi-objective optimization model for the design of water distribution network (WDN). Reliability and cost are two contradicting objectives that optimized. The evolutionary technique multi-objective (MO) Jaya, hereafter referred as MO-JAYANET, is developed optimal WDN. EPANET used hydraulic solver in this study. concept constraint violation, dominance, non-domi...

Real world problems often present multiple, frequently conflicting, objectives. The research for optimal solutions of multi-objective problems can be achieved through means of genetic algorithms, which are inspired by the natural process of evolution: an initial population of solutions is randomly generated, then pairs of solutions are selected and combined in order to create new solutions slig...

Abstract Multi-objective meta-heuristics are used to optimize water distribution networks (WDNs) as they can achieve a near-optimal balance between cost and resilience in unified platform. Most of these algorithms include tuning algorithm-specific control parameters for higher optimization efficiency, leading an increased computational effort. The current study is inspired by the desire address...

Abstract This paper introduces a multi-objective variant of the marine predators algorithm (MPA) called improved (MOIMPA), which incorporates concepts from Quantum theory. By leveraging theory, MOIMPA aims to enhance MPA’s ability balance between exploration and exploitation find optimal solutions. The utilizes concept inspired by Schrödinger wave function determine position particles in search...