Pumping Optimization of Coastal Aquifers Assisted by Adaptive Metamodelling Methods and Radial Basis Functions

Christelis, Vasileios; Mantoglou, Aristotelis

doi:10.1007/s11269-016-1337-3

Cited by 61 publications

(23 citation statements)

References 41 publications

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“…Rao et al [48] used the ANNs as the surrogate model to replace the SEAWAT model and combined it with the simulated annealing algorithm (SA) to solve the management problems of seawater intrusion. Christelis and Mantoglou [49] used the radial basis functions (RBF) as a surrogate model to emulate the scalar response of a multivariate function which can reduce 96% of computational time and combined RBF with evolutionary annealing-simplex algorithm in a pumping optimization problem.…”

Section: Introductionmentioning

confidence: 99%

A Simulation-Optimization Model for Seawater Intrusion Management at Pingtung Coastal Area, Taiwan

Huang

Chiu

2018

Water

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The coastal regions of Pingtung Plain in southern Taiwan rely on groundwater as their main source of fresh water for aquaculture, agriculture, domestic, and industrial sectors. The availability of fresh groundwater is threatened by unsustainable groundwater extraction and the over-pumpage leads to the serious problem of seawater intrusion. It is desired to find appropriate management strategies to control groundwater salinity and mitigate seawater intrusion. In this study, a simulation-optimization model has been presented to solve the problem of seawater intrusion along the coastal aquifers in Pingtung Plain and the objective is using injection well barriers and minimizing the total injection rate based on the predetermined locations of injection barriers. The SEAWAT code is used to simulate the process of seawater intrusion and the surrogate model of artificial neural networks (ANNs) is used to approximate the seawater intrusion (SWI) numerical model to increase the computational efficiency during the optimization process. The heuristic optimization scheme of differential evolution (DE) algorithm is selected to identify the global optimal management solution. Two different management scenarios, one is the injection barriers located along the coast and the other is the injection barrier located at the inland, are considered and the optimized results show that the deployment of injection barriers at the inland is more effective to reduce total dissolved solids (TDS) concentrations and mitigate seawater intrusion than that along the coast. The computational time can be reduced by more than 98% when using ANNs to replace the numerical model and the DE algorithm has been confirmed as a robust optimization scheme to solve groundwater management problems. The proposed framework can identify the most reliable management strategies and provide a reference tool for decision making with regard to seawater intrusion remediation.

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Section: Introductionmentioning

confidence: 99%

A Simulation-Optimization Model for Seawater Intrusion Management at Pingtung Coastal Area, Taiwan

Huang

Chiu

2018

Water

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“…These two interpolation models are among the most popular ones for feasibility analysis and optimization by virtue of their capability to provide a quantitative measure of prediction uncertainty. This has allowed these models to prevail in many applications, such as design simulation [196] and pharmaceutical process simulations [197] in the case of Kriging, and parameter estimation [198] or water pumping optimization [199] in the case of RBF.…”

Section: Surrogate Model Assisted Optimizationmentioning

confidence: 99%

Bio-inspired computation: Where we stand and what's next

Ser

Osaba

Molina

et al. 2019

Swarm and Evolutionary Computation

481

106

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“…Furthermore, over recent decades, novel modeling techniques have been developed which can substantially aid the optimization of process systems. For instance, surrogate models such as Kriging [39][40][41][42][43][44], radial basis functions [45][46][47][48][49][50], artificial neural networks [51][52][53][54][55][56], splines [57,58], among others were shown to accurately represent complex physical systems while aiding optimal search algorithms. No literature exists which explores the application of such techniques to advance the study of CHP dispatch.…”

Section: Optimal Combined Heat and Power Dispatchmentioning

confidence: 99%

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

Kazda¹,

Li²

2020

Processes

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Combined heat and power (CHP) systems are attracting increasing attention for their ability to improve the economics and sustainability of the electricity system. Determining how to best operate these systems is difficult because they can consist of many generating units whose operation is governed by complex nonlinear physics. Mathematical programming is a useful tool to support the operation of CHP systems, and has been the subject of substantial research attention since the early 1990s. This paper critically reviews the modeling and optimization work that has been done on the CHP economic dispatch problem, and the CHP economic and emission dispatch problem. A summary of the common models used for these problems is provided, along with comments on future modeling work that would beneficial to the field. The majority of optimization approaches studied for CHP system operation are metaheuristic algorithms. A discussion of the limitations and benefits of metaheuristic algorithms is given. Finally, a case study optimizing five classic CHP system test instances demonstrates the advantages of the using deterministic global search algorithms over metaheuristic search algorithms.

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Pumping Optimization of Coastal Aquifers Assisted by Adaptive Metamodelling Methods and Radial Basis Functions

Cited by 61 publications

References 41 publications

A Simulation-Optimization Model for Seawater Intrusion Management at Pingtung Coastal Area, Taiwan

A Simulation-Optimization Model for Seawater Intrusion Management at Pingtung Coastal Area, Taiwan

Bio-inspired computation: Where we stand and what's next

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

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