Optimal groundwater remediation design of pump and treat systems via a simulation–optimization approach and firefly algorithm

Abstract

In the present study, an optimization approach based on the firefly algorithm (FA) is combined with a finite element simulation method (FEM) to determine the optimum design of pump and treat remediation systems. Three multi-objective functions in which pumping rate and clean-up time are design variables are considered and the proposed FA-FEM model is used to minimize operating costs, total pumping volumes and total pumping rates in three scenarios while meeting water quality requirements. The groundwater lift and contaminant concentration are also minimized through the optimization process. The obtained results show the applicability of the FA in conjunction with the FEM for the optimal design of groundwater remediation systems. The performance of the FA is also compared with the genetic algorithm (GA) and the FA is found to have a better convergence rate than the GA.

Hybrid Optimization Algorithms of Firefly with GA and PSO for the Optimal Design of Water Distribution Networks

“…However, the algorithm could fall into a locally optimal solution or suffer from low accuracy when solving high-dimensional optimization problems [32]. The algorithm has been applied to many problems related to water resources engineering [33][34][35][36]. Up to the knowledge of the authors, the firefly algorithm has not yet been applied for the least cost design of water distribution systems.…”

Shape optimization of flow split ducting elements using an improved Box complex method

“…Shape definition is often carried out using parametric equations (Joodaki and Ashrafizadeh 2014;Samareh 1999) as most shapes are intrinsically independent of any coordinate system. Various optimization techniques have been used to search for the optimal configuration of fluid flow equipment, for example, gradient-based optimization techniques, global optimization by dimensionality reduction techniques such as the Karhunen-Loève expansion and evolutionary approaches such as genetic algorithms, particle swarm optimization (a method which shares many features with genetic algorithms), firefly algorithms and surface methods (Avvari and Jayanti 2013;Chen et al 2015;Diez, Campana, and Stern 2015;Elsayed and Lacor 2013;Eyi and Yumuşak 2015;Kazemzadeh-Parsi et al 2015;Raghavan et al 2013;Safikhani, Hajiloo, and Ranjbar 2011;Said et al 2015;Tesch and Kaczorowska 2015).…”

Inexact multi-attribute decision analysis of groundwater remediation strategies with inputs of interval data

“…The condition is potential, imperceptible, persistence, toxicity and long-range migration. As one of the most widely physical method, pump and treat (P&T) can remove contaminants directly through flushing and collecting the contaminants from a highly risky zone [3,4].…”