Multi-objective optimization of in-situ bioremediation of groundwater using a hybrid metaheuristic technique based on differential evolution, genetic algorithms and simulated annealing

• Autorzy: Kumar D. , Ch S. , Mathur S. , Adamowski J.

Identyfikatory

DOI

10.1515/jwld-2015-0022

Warianty tytułu

PL

Wielozadaniowa optymalizacja bioremediacji wód gruntowych in situ z zastosowaniem hybrydowej techniki metaheurystycznej opartej na zróżnicowanej ewolucji, algorytmach genetycznych i symulowanym wyżarzaniu

• Języki publikacji: EN

Abstrakty

EN

Groundwater contamination due to leakage of gasoline is one of the several causes which affect the groundwater environment by polluting it. In the past few years, In-situ bioremediation has attracted researchers because of its ability to remediate the contaminant at its site with low cost of remediation. This paper proposed the use of a new hybrid algorithm to optimize a multi-objective function which includes the cost of remediation as the first objective and residual contaminant at the end of the remediation period as the second objective. The hybrid algorithm was formed by combining the methods of Differential Evolution, Genetic Algorithms and Simulated Annealing. Support Vector Machines (SVM) was used as a virtual simulator for biodegradation of contaminants in the groundwater flow. The results obtained from the hybrid algorithm were compared with Differential Evolution (DE), Non Dominated Sorting Genetic Algorithm (NSGA II) and Simulated Annealing (SA). It was found that the proposed hybrid algorithm was capable of providing the best solution. Fuzzy logic was used to find the best compromising solution and finally a pumping rate strategy for groundwater remediation was presented for the best compromising solution. The results show that the cost incurred for the best compromising solution is intermediate between the highest and lowest cost incurred for other non-dominated solutions.

PL

Zanieczyszczenie wód gruntowych wyciekami benzyny jest jedną z kilku przyczyn wpływających na środowisko wód podziemnych. W ostatnich latach bioremediacja in situ przyciągała uwagę badaczy z powodu jej zdolności do usuwania zanieczyszczeń w ich siedlisku i niskich kosztów procesu. Przedstawiona praca proponuje użycie nowego algorytmu hybrydowego do optymalizacji wielozadaniowej funkcji, która obejmuje koszty remediacji jako pierwsze zadanie i resztową zawartość zanieczyszczeń po zakończeniu procesu jako drugie z zadań. Algorytm hybrydowy powstał z połączenia metod różnicowej ewolucji, algorytmu genetycznego i symulowanego wyżarzania. Maszyna wektorów nośnych (SVM) została użyta jako wirtualny symulator biologicznej degradacji zanieczyszczeń w wodach gruntowych. Wyniki uzyskane z algorytmy hybrydowego porównano z wynikami zróżnicowanej ewolucji (DE), algorytmu genetycznego (NSGA II) i symulowanego wyżarzania (SA). Stwierdzono, że proponowany algorytm był w stanie zapewnić najlepsze rozwiązanie. Użyto metody z zakresu logiki rozmytej dla znalezienia najlepszego rozwiązania kompromisowego i na końcu przedstawiono dla tego rozwiązania strategię szybkości pompowania celem remediacji wód gruntowych. Wyniki pokazały, że koszty ponoszone na rozwiązanie kompromisowe są pośrednie między najwyższymi i najniższymi kosztami innych rozwiązań.

Słowa kluczowe

EN

differential evolution; fuzzy logic; genetic algorithm; groundwater; hybrid algorithm; in situ bioremediation; simulated annealing; support vector machine (SVM)

PL

bioremediacja in situ; algorytm hybrydowy; algorytm genetyczny; logika rozmyta; maszyna wektorów nośnych SVM; wyżarzanie symulowane; wody gruntowe; zróżnicowana ewolucja

• Wydawca: Wydawnictwo ITP
• Czasopismo: Journal of Water and Land Development
• Rocznik: 2015
• Tom: no. 27
• Strony: 29--40
• Opis fizyczny: Bibliogr. 53 poz., rys., tab.

Twórcy

autor

Kumar D.

• Indian Institute of Technology in Delhi, India

autor

Ch S.

• Indian Institute of Technology in Delhi, India

autor

Mathur S.

• Indian Institute of Technology in Delhi, India

autor

Adamowski J.

• McGill University, Faculty of Agricultural and Environmental Sciences, Department of Bioresource Engineering, Quebec, Canada, H9X 3V9

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.