Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA)

Erickson, Mark; Mayer, Alex; Horn, Jeffrey

doi:10.1016/s0309-1708(01)00020-3

Cited by 141 publications

(55 citation statements)

References 18 publications

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“…To handle this burden, Rao et al (2003Rao et al ( , 2004 and Kourakos (2009) used artificial neural networks in the optimization, that tend to give an efficient approximate solution, but do not eliminate the localoptima problem. In some instances, authors opted for a multi-objective optimization (Erickson et al, 2002;Maskey et al, 2002;Park & Aral, 2004;Mantoglou & Kourakos, 2007;Ricciardi et al, 2007). In our screening model, we opted for backward dynamic programming (DP), heuristically modified to avoid convergence to local optima; our model considers variable-density transient flow, instead of the oftenused sharp-interface approximation and steady flow (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Cost-efficient management of coastal aquifers via recharge with treated wastewater and desalination of brackish groundwater: general framework

Koussis

Georgopoulou

Kotronarou

et al. 2010

Hydrological Sciences Journal

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. (2010) Cost-efficient management of coastal aquifers via recharge with treated wastewater and desalination of brackish groundwater: general framework. Hydrol. Sci. J. 55(7),1217-1233.Abstract Semi-arid coastal zones often suffer water-stress, as water demand is high and markedly seasonal, due to agriculture and tourism. Driven by scarcity of surface water, the communities in semi-arid coastal regions turn to aquifers as prime water source; but intensive exploitation of coastal aquifers causes seawater intrusion, which degrades the quality of groundwater. The cost-efficient and sustainable development of coastal aquifers can be achieved through a holistic management scheme which combines two non-traditional water sources: (a) saltwater, to be treated to the desired quality, and (b) wastewater, to be re-claimed to augment aquifer recharge for control of seawater intrusion, and also to meet certain demands. This management scheme is based on the idea that it is costadvantageous to: (i) desalt brackish groundwater, instead of seawater, as the former requires far less energy, and (ii) to re-use wastewater at only the differential cost to any treatment already practiced. In this paper, we present the general framework of the proposed management scheme, and a decision aid tool (DAT) which has been developed to assist decision makers to explore the scheme's decision space. The DAT uses cost as optimization criterion to screen various management scenarios, via modelling of the dynamic natural-engineered system behaviour, and identifies those cost-efficient ones that meet the water demand and achieve aquifer protection.Key words aquifer; brackish groundwater; coastal; cost; decision aid; desalination; optimization; recharge; sea intrusion; sustainable; water management; wastewater Gestion économe des aquifères côtiers via la recharge d'eaux usées traitées et la désalinisation d'eaux souterraines saumâtres: cadre général Résumé Les zones côtières semi-arides souffrent fréquemment de stress hydrique, dans la mesure où la demande en eau est élevée et particulièrement saisonnière, en lien avec l'agriculture et le tourisme. Poussées par la rareté des eaux de surface, les communautés des régions côtières semi-arides considèrent les aquifères comme étant les principales ressources en eau; mais une exploitation intensive des aquifères côtiers engendre des intrusions marines qui dégradent la qualité des eaux souterraines. Le développement économe et durable des aquifères côtiers peut être conduit grâce à un schéma de gestion holistique qui combine deux ressources non conventionnelles: (a) les eaux salées, à traiter pour atteindre la qualité escomptée, et (b) les eaux usées à traiter pour augmenter la recharge des aquifères et ainsi contrôler les intrusions marines et satisfaire certaines demandes. Ce schéma de gestion est basé sur l'idée qu'il est économiquement avantageux de: (i) désaler les eaux souterraines saumâtres, plutôt que les eaux marines, puisque cela nécessite bien moins d'énergie, et (ii) réutiliser les eaux usées u...

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Section: Literature Reviewmentioning

confidence: 99%

Cost-efficient management of coastal aquifers via recharge with treated wastewater and desalination of brackish groundwater: general framework

Koussis

Georgopoulou

Kotronarou

et al. 2010

Hydrological Sciences Journal

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“…There is a growing body of water resources literature (Horn and Nafpliotis, 1993;Ritzel et al, 1994;Cieniawski et al, 1995;Halhal et al, 1997;Loughlin et al, 2000;Reed et al, 2001;Erickson et al, 2002;Reed and Minsker, 2004) demonstrating the importance of multiobjective problems (MOPs) and evolutionary multiobjective solution tools. A key characteristic of MOPs is that optimization cannot consider a single objective because performance in other objectives may suffer.…”

Section: Multiobjective Optimization Terminologymentioning

confidence: 99%

How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?

Tang

Reed

Wagener

2006

Hydrol. Earth Syst. Sci.

174

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Abstract. This study provides a comprehensive assessment of state-of-the-art evolutionary multiobjective optimization (EMO) tools' relative effectiveness in calibrating hydrologic models. The relative computational efficiency, accuracy, and ease-of-use of the following EMO algorithms are tested: Epsilon Dominance Nondominated Sorted Genetic Algorithm-II (ε-NSGAII), the Multiobjective Shuffled Complex Evolution Metropolis algorithm (MOSCEM-UA), and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). This study uses three test cases to compare the algorithms' performances: (1) a standardized test function suite from the computer science literature, (2) a benchmark hydrologic calibration test case for the Leaf River near Collins, Mississippi, and (3) a computationally intensive integrated surface-subsurface model application in the Shale Hills watershed in Pennsylvania. One challenge and contribution of this work is the development of a methodology for comprehensively comparing EMO algorithms that have different search operators and randomization techniques. Overall, SPEA2 attained competitive to superior results for most of the problems tested in this study. The primary strengths of the SPEA2 algorithm lie in its search reliability and its diversity preservation operator. The biggest challenge in maximizing the performance of SPEA2 lies in specifying an effective archive size without a priori knowledge of the Pareto set. In practice, this would require significant trial-and-error analysis, which is problematic for more complex, computationally intensive calibration applications. ε-NSGAII appears to be superior to MOSCEM-UA and competitive with SPEA2 for hydrologic model calibration. ε-NSGAII's primary strength lies in its ease-of-use due to its dynamic population sizing and archiving which lead to rapid convergence to very high quality solutions with minimal user input. MOSCEM-UA is best suited for hydrologic model calibration applications that have small parameter sets and small Correspondence to: P. Reed (preed@engr.psu.edu) model evaluation times. In general, it would be expected that MOSCEM-UA's performance would be met or exceeded by either SPEA2 or ε-NSGAII.

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“…Ritzel et al (1994) used a genetic algorithm to solve a multi-objective groundwater pollution containment problem (vector-evaluated GA and Pareto GA). Erickson et al (2002) used a niched Pareto genetic algorithm for the optimization of a pump-and-treat system that simultaneously minimizes the remedial cost and the contaminant mass which remains at the end of the remediation period. McPhee and Yeh (2006) developed an experimental design-based methodology for groundwater management using multi-objective programming for parameter estimation that was solved by combination of a genetic algorithm and gradient-based optimization techniques.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization for free-phase LNAPL recovery using evolutionary computation algorithms

Dokou

Karatzas

2013

Hydrological Sciences Journal

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A nonlinear, multi-objective optimization methodology is presented that seeks to maximize free product recovery of light non-aqueous phase liquids (LNAPLs) while minimizing operation cost, by introducing the novel concept of optimal alternating pumping and resting periods. This process allows more oil to flow towards the extraction wells, ensuring maximum free product removal at the end of the remediation period with minimum groundwater extraction. The methodology presented here combines FEHM (Finite Element Heat and Mass transfer code), a multiphase groundwater model that simulates LNAPL transport, with three evolutionary algorithms: the genetic algorithm (GA), the differential evolution (DE) algorithm and the particle swarm optimization (PSO) algorithm. The proposed optimal free-phase recovery strategy was tested using data from a field site, located near Athens, Greece. The PSO and DE solutions were very similar, while that provided by the GA was inferior, although the computation time was roughly the same for all algorithms. One of the most efficient algorithms (PSO) was chosen to approximate the optimal Pareto front, a method that provides multiple options to decision makers. When the optimal strategy is implemented, although a significant amount of LNAPL free product is captured, a spreading of the LNAPL plume occurs.Key words free product LNAPL recovery; multi-objective optimization; Pareto front; genetic algorithm; differential evolution; particle swarm optimization Optimisation multi-objectif utilisant des algorithmes d'évolution pour la récupération de LLPNA libres Résumé Nous présentons une méthode d'optimisation non-linéaire et multi-objectif visant à maximiser la récupération de liquides légers en phase non aqueuse (LLPNA) tout en minimisant les coûts d'exploitation, en introduisant une nouvelle stratégie de périodes optimales de pompage et de pause alternées. Ce procédé permet l'écoulement de davantage de pétrole vers les puits d'extraction, et assure une élimination maximum de produit à la fin de la période de dépollution tout en minimisant l'extraction d'eaux souterraines. La méthodologie présen-tée ici combine FEHM, un modèle d'écoulement souterrain multiphasique simulant le transport des LLPNA, avec trois algorithmes d'évolution: l'algorithme génétique (AG), l'algorithme à évolution différentielle (ED) et l'optimisation par essaims particulaires (OEP). Cette stratégie de récupération a été testée à l'aide des données d'un site situé près d'Athènes, en Grèce. Les solutions de l'OEP et l'ED étaient très similaires tandis que celle de l'AG était moins intéressante, alors que le temps d'exécution était à peu près le même pour tous les algorithmes. L'algorithme le plus performant (OEP) a été choisi pour se rapprocher du front de Pareto optimal, méthode qui offre plusieurs options aux décideurs. Lorsque la stratégie optimale est mise en oeuvre, même si une quantité importante de LLPNA est récupérée, on observe cependant la propagation d'un panache de LLPNA.Mots clefs récupération de LLPNA li...

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Multi-objective optimal design of groundwater remediation systems: application of the niched Pareto genetic algorithm (NPGA)

Cited by 141 publications

References 18 publications

Cost-efficient management of coastal aquifers via recharge with treated wastewater and desalination of brackish groundwater: general framework

Cost-efficient management of coastal aquifers via recharge with treated wastewater and desalination of brackish groundwater: general framework

How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?

Multi-objective optimization for free-phase LNAPL recovery using evolutionary computation algorithms

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