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Comparison of constraint-handling mechanisms for sewer optimization

Year 2024, Volume: 13 Issue: 1, 139 - 148, 15.01.2024
https://doi.org/10.28948/ngumuh.1318989

Abstract

The aim of this study is to investigate the most appropriate constraint-handling mechanism in the sewer hydraulic design optimization problem. For this purpose, Dandelion Optimizer, which has not been used before to solve this problem, was used. Since the considered problem is a constrained optimization problem, constraint-handling mechanisms are required to solve this problem. In this study, the effects of various constraint-handling mechanisms on the performance of the algorithm were investigated in two different sized sewer networks. The constraint-handling mechanisms used are static penalty method, dynamic penalty method, dynamic penalty method with the superiority of feasible points, exponential dynamic penalty method, exponential dynamic penalty method with the superiority of feasible points, eclectic penalty method, adaptive penalty method and inverse tangent method. Solution quality, solution time and progress ratio were used as performance criteria. The most consistent result among the constraint-handling mechanisms discussed, was the adaptive penalty method.

References

  • L. W. Mays and B. C. Yen, Optimal cost design of branched sewer systems. Water Resources Research, 12(1), 37–47, 1975.
  • L. W. Mays and H. G. Wenzel, Optimal design of multilevel branching sewer systems. Water Resources Research, 12(5), 913–917, 1976.
  • L. Y. Liang, R. G. Tompson, and D. M. Young, Optimising the design of sewer networks using genetic algorithms and tabu search. Engineering, Construction and Architectural Management, 11(2), 101–112, 2004. https://doi.org/10.1108/ 09699980410527849.
  • M. H. Afshar, A. Afshar, M. A. Mariño, and A. A. S. Darbandi, Hydrograph-based storm sewer design optimization by genetic algorithm. Canadian Journal of Civil Engineering, 33(3), 319–325, 2006. https://doi.org/10.1139/L05-121.
  • T.-C. Pan and J.-J. Kao, GA-QP model to optimize sewer system design. Journal of Environmental Engineering, 135(1), 17–24, 2009. https://doi.org/10.1061/(ASCE)07339372(2009)135:1(17).
  • M. H. Afshar, A parameter free continuous ant colony optimization algorithm for the optimal design of storm sewer networks: constrained and unconstrained approach. Advances in Engineering Software, 41(2), 188–195, 2010. https://doi.org/10.1016/ j.advengsoft.2009.09.009.
  • T. Cetin and M. A. Yurdusev, Genetic algorithm for networks with dynamic mutation rate. Gradevinar, 69(12), 1101–1109, 2018. https://doi.org/10.14256/ JCE.1533.2015.
  • Masoumi, F., S. Masoumzadeh, N. Zafari, and M.J.E. Skardi, Optimum sanitary sewer network design using shuffled gray wolf optimizer. Journal of Pipeline Systems Engineering and Practice 12(4): 04021055, 2021. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000597.
  • A. Gholami, P. G. Durgut and M. T. Ayvaz, An integrated simulation-optimization approach for dynamic design of the urban wastewater collection systems. Turkish Journal of Civil Engineering, 2023 105-134, 719, 2023. https://doi.org/10.18400/ tjce.1209180.
  • K. N. Praveen and Y. P. Mathur, Application of graph theory for optimal sewer layout generation. Discovery, 40(183), 151-157, 2015.
  • A. E. Bakhshipour, M. Bakhshizadeh, U. Dittmer, W. Nowak, and A. Haghighi, A graph-theory based algorithm to generate decentralized urban drainage layouts. Green, 633–637, 2018. https://doi.org/ 10.1007/978-3-319-99867-1_109.
  • N. de Villiers, G. C. van Rooyen and M. Middendorf, Sewer network design layout optimisation using ant colony algorithms. Journal of the South African Institution of Civil Engineers, 60(3), September 2018, 2–15, 1773, 2018. https://doi.org/10.17159/2309-8775/2018/v60n3a1.
  • G. P. W. Rodrigues, L. H. M. Costa, G. M. Farias and M. A. H. de Castro, A depth-first search algorithm for optimizing the gravity pipe networks layout. Water Resources Management, 33,4583–4598, 2019. https://doi.org/10.1007/s11269-019-02373-x.
  • M. E. Turan, G. Bacak-Turan, T. Cetin and E. Aslan, Feasible sanitary sewer network generation using graph theory. Advances in Civil Engineering, 2019, 8527180, 15, 2019. https://doi.org/10.1155/2019/8527180.
  • G. Li and R. G. S. Matthew, New approach for optimization of urban drainage systems. Journal of Environmental Engineering, 116(5),927–944, 1990. https://doi.org/10.1061/(ASCE)07339372(1990)116:5(927) .
  • A. F. Diogo and V. M. Graveto, Optimal layout of sewer systems: a deterministic versus a stochastic model. Journal of Hydraulic Engineering, 132(9), 927–943, 2006. https://doi.org/10.1061/(ASCE)0733-9429(2006)132:9(927).
  • N. Duque, D. Duque, A. Aguilar and J. Saldarriaga, Sewer network layout selection and hydraulic design using a mathematical optimization framework. Water, 12, 3337, 2020. https://doi.org/10.3390/w12123337.
  • F. M. Alfaisal and L. W. Mays, Optimization models for layout and pipe design for storm sewer systems. Water Resources Management, 35,4841–4854, 2021. https://doi.org/10.1007/s11269-021-02958-5.
  • E. Tan, D. Sadak, and M.T. Ayvaz, Kanalizasyon sistemlerinin diferansiyel evrim algoritması kullanılarak optimum tasarımı. Teknik Dergi, 31(5), 10229-10250, 2020. https://doi.org/10.18400/ tekderg.541507.
  • M. Çunkaş, and A. Ürkmez, Çok kriterli bulanık genetik algoritma ile dalgıç asenkron motorların tasarım optimizasyonu. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 23(3), 2008.
  • Z. Garip, M.E. Çimen, and A. F. Boz, Harris şahinleri ve balina optimizasyon algoritmalarının kısıt işleme teknikleriyle uygulaması: Karşılaştırmalı bir çalışma. Journal of Intelligent Systems: Theory and Applications, 4(2), 76-85, 2021. https://doi.org/ 10.38016/jista.857881.
  • A. Baykasoğlu, and F.B. Ozsoydan, Adaptive firefly algorithm with chaos for mechanical design optimization problems. Applied soft computing, 36, 152-164, 2015. https://doi.org/10.1016/ j.asoc.2015.06.056.
  • M.F. Tasgetiren, A Genetic Algorithm with an Adaptive Penalty Function for the Orienteering Problem. Journal of Economic & Social Research, 4(2), 2002.
  • G. Iyengar, and K. Sigman, Exponential penalty function control of loss networks. The Annals of Applied Probability, 14(4), 1698–1740, 2004. https://doi.org/10.1214/105051604000000936.
  • İ. Gölcük, A comparative analysis of constraint-handling mechanisms for solving engineering design problems. Endüstri Mühendisliği, 32(2), 201-216, 2021. http://orcid.org/0000-0002-8430-7952.
  • O. Kramer, A review of constraint-handling techniques for evolution strategies. Applied Computational Intelligence and Soft Computing, 1-19, 2010. https://doi.org/10.1155/2010/185063.
  • M. Y. Ameca-Alducin, M. Hasani-Shoreh, W. Blaikie, F. Neumann and E. Mezura-Montes, A comparison of constraint handling techniques for dynamic constrained optimization problems. 2018 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE, 2018. https://doi.org/10.1109/CEC.2018.8477750.
  • S. Zhao, T. Zhang, S. Ma and M. Chen, Dandelion optimizer: a nature-inspired metaheuristic algorithm for engineering applications. Engineering Applications of Artificial Intelligence, 114, 105075, 2022. https://doi.org/10.1016/j.engappai.2022.105075.
  • D. Simon, Evolutionary optimization algorithms. John Wiley & Sons, 2013.
  • T. H. Kim, I. Maruta, and T. Sugie, A simple and efficient constrained particle swarm optimization and its application to engineering design problems. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 224(2), 389-400, 2010. https://doi.org/ 10.1243/09544062JMES1732.
  • R. Moeini and M. H. Afshar, Layout and size optimization of sanitary sewer network using intelligent ants. Advances in Engineering Software 51,49–62, 2012. https://doi.org/ 10.1016/j.advengsoft.2012.05.003.
  • R. Moeini and M. H. Afshar, Arc based ant colony optimization algorithm for optimal design of gravitational sewer networks. Ain Shams Engineering Journal 8, 207–223, 2017. https://doi.org/ 10.1016/j.asej.2016.03.003.
  • M. Mansouri, M. Khanjani, Optimization of sewer networks using nonlinear programming. J Water Wastewater, 10(2), 20-30,1999.
  • W. H. Hassan, M. H. Jassem, and S. S. Mohammed, A GA-HP model for the optimal design of sewer networks. Water Resources Management 32:865-879, 2018. https://doi.org/10.1007/s11269-017-1843-y.

Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması

Year 2024, Volume: 13 Issue: 1, 139 - 148, 15.01.2024
https://doi.org/10.28948/ngumuh.1318989

Abstract

Bu çalışmanın amacı kanalizasyon hidrolik tasarım optimizasyonu probleminde en uygun kısıt yönetimi mekanizmasını araştırmaktır. Bu amaçla problemin çözümünde daha önce kullanılmamış olan Karahindiba Optimizasyon Algoritması kullanılmıştır. Ele alınan problem kısıtlı optimizasyon problemi olduğundan, problemin çözümünde kısıt yönetimi mekanizmalarına ihtiyaç duyulmaktadır. Çalışmada çeşitli kısıt yönetimi mekanizmalarının, algoritmanın performansı üzerindeki etkileri iki farklı boyuttaki kanalizasyon şebekesinde araştırılmıştır. Kullanılan kısıt yönetimi mekanizmaları statik ceza yöntemi, dinamik ceza yöntemi, olurlu çözümlerin üstünlüğü ile birleştirilmiş dinamik ceza yöntemi, üstel dinamik ceza yöntemi, olurlu çözümlerin üstünlüğü ile birleştirilmiş üstel dinamik ceza yöntemi, eklektik ceza yöntemi, uyarlanabilir ceza yöntemi ve ters tanjant yöntemidir. Performans ölçütü olarak çözüm kalitesi, çözüm süresi ve gelişme oranı ölçütleri kullanılmıştır. Ele alınan kısıt yönetimi mekanizmalarından en tutarlı sonuca sahip olan yöntem, uyarlanabilir ceza yöntemi olmuştur.

References

  • L. W. Mays and B. C. Yen, Optimal cost design of branched sewer systems. Water Resources Research, 12(1), 37–47, 1975.
  • L. W. Mays and H. G. Wenzel, Optimal design of multilevel branching sewer systems. Water Resources Research, 12(5), 913–917, 1976.
  • L. Y. Liang, R. G. Tompson, and D. M. Young, Optimising the design of sewer networks using genetic algorithms and tabu search. Engineering, Construction and Architectural Management, 11(2), 101–112, 2004. https://doi.org/10.1108/ 09699980410527849.
  • M. H. Afshar, A. Afshar, M. A. Mariño, and A. A. S. Darbandi, Hydrograph-based storm sewer design optimization by genetic algorithm. Canadian Journal of Civil Engineering, 33(3), 319–325, 2006. https://doi.org/10.1139/L05-121.
  • T.-C. Pan and J.-J. Kao, GA-QP model to optimize sewer system design. Journal of Environmental Engineering, 135(1), 17–24, 2009. https://doi.org/10.1061/(ASCE)07339372(2009)135:1(17).
  • M. H. Afshar, A parameter free continuous ant colony optimization algorithm for the optimal design of storm sewer networks: constrained and unconstrained approach. Advances in Engineering Software, 41(2), 188–195, 2010. https://doi.org/10.1016/ j.advengsoft.2009.09.009.
  • T. Cetin and M. A. Yurdusev, Genetic algorithm for networks with dynamic mutation rate. Gradevinar, 69(12), 1101–1109, 2018. https://doi.org/10.14256/ JCE.1533.2015.
  • Masoumi, F., S. Masoumzadeh, N. Zafari, and M.J.E. Skardi, Optimum sanitary sewer network design using shuffled gray wolf optimizer. Journal of Pipeline Systems Engineering and Practice 12(4): 04021055, 2021. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000597.
  • A. Gholami, P. G. Durgut and M. T. Ayvaz, An integrated simulation-optimization approach for dynamic design of the urban wastewater collection systems. Turkish Journal of Civil Engineering, 2023 105-134, 719, 2023. https://doi.org/10.18400/ tjce.1209180.
  • K. N. Praveen and Y. P. Mathur, Application of graph theory for optimal sewer layout generation. Discovery, 40(183), 151-157, 2015.
  • A. E. Bakhshipour, M. Bakhshizadeh, U. Dittmer, W. Nowak, and A. Haghighi, A graph-theory based algorithm to generate decentralized urban drainage layouts. Green, 633–637, 2018. https://doi.org/ 10.1007/978-3-319-99867-1_109.
  • N. de Villiers, G. C. van Rooyen and M. Middendorf, Sewer network design layout optimisation using ant colony algorithms. Journal of the South African Institution of Civil Engineers, 60(3), September 2018, 2–15, 1773, 2018. https://doi.org/10.17159/2309-8775/2018/v60n3a1.
  • G. P. W. Rodrigues, L. H. M. Costa, G. M. Farias and M. A. H. de Castro, A depth-first search algorithm for optimizing the gravity pipe networks layout. Water Resources Management, 33,4583–4598, 2019. https://doi.org/10.1007/s11269-019-02373-x.
  • M. E. Turan, G. Bacak-Turan, T. Cetin and E. Aslan, Feasible sanitary sewer network generation using graph theory. Advances in Civil Engineering, 2019, 8527180, 15, 2019. https://doi.org/10.1155/2019/8527180.
  • G. Li and R. G. S. Matthew, New approach for optimization of urban drainage systems. Journal of Environmental Engineering, 116(5),927–944, 1990. https://doi.org/10.1061/(ASCE)07339372(1990)116:5(927) .
  • A. F. Diogo and V. M. Graveto, Optimal layout of sewer systems: a deterministic versus a stochastic model. Journal of Hydraulic Engineering, 132(9), 927–943, 2006. https://doi.org/10.1061/(ASCE)0733-9429(2006)132:9(927).
  • N. Duque, D. Duque, A. Aguilar and J. Saldarriaga, Sewer network layout selection and hydraulic design using a mathematical optimization framework. Water, 12, 3337, 2020. https://doi.org/10.3390/w12123337.
  • F. M. Alfaisal and L. W. Mays, Optimization models for layout and pipe design for storm sewer systems. Water Resources Management, 35,4841–4854, 2021. https://doi.org/10.1007/s11269-021-02958-5.
  • E. Tan, D. Sadak, and M.T. Ayvaz, Kanalizasyon sistemlerinin diferansiyel evrim algoritması kullanılarak optimum tasarımı. Teknik Dergi, 31(5), 10229-10250, 2020. https://doi.org/10.18400/ tekderg.541507.
  • M. Çunkaş, and A. Ürkmez, Çok kriterli bulanık genetik algoritma ile dalgıç asenkron motorların tasarım optimizasyonu. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 23(3), 2008.
  • Z. Garip, M.E. Çimen, and A. F. Boz, Harris şahinleri ve balina optimizasyon algoritmalarının kısıt işleme teknikleriyle uygulaması: Karşılaştırmalı bir çalışma. Journal of Intelligent Systems: Theory and Applications, 4(2), 76-85, 2021. https://doi.org/ 10.38016/jista.857881.
  • A. Baykasoğlu, and F.B. Ozsoydan, Adaptive firefly algorithm with chaos for mechanical design optimization problems. Applied soft computing, 36, 152-164, 2015. https://doi.org/10.1016/ j.asoc.2015.06.056.
  • M.F. Tasgetiren, A Genetic Algorithm with an Adaptive Penalty Function for the Orienteering Problem. Journal of Economic & Social Research, 4(2), 2002.
  • G. Iyengar, and K. Sigman, Exponential penalty function control of loss networks. The Annals of Applied Probability, 14(4), 1698–1740, 2004. https://doi.org/10.1214/105051604000000936.
  • İ. Gölcük, A comparative analysis of constraint-handling mechanisms for solving engineering design problems. Endüstri Mühendisliği, 32(2), 201-216, 2021. http://orcid.org/0000-0002-8430-7952.
  • O. Kramer, A review of constraint-handling techniques for evolution strategies. Applied Computational Intelligence and Soft Computing, 1-19, 2010. https://doi.org/10.1155/2010/185063.
  • M. Y. Ameca-Alducin, M. Hasani-Shoreh, W. Blaikie, F. Neumann and E. Mezura-Montes, A comparison of constraint handling techniques for dynamic constrained optimization problems. 2018 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE, 2018. https://doi.org/10.1109/CEC.2018.8477750.
  • S. Zhao, T. Zhang, S. Ma and M. Chen, Dandelion optimizer: a nature-inspired metaheuristic algorithm for engineering applications. Engineering Applications of Artificial Intelligence, 114, 105075, 2022. https://doi.org/10.1016/j.engappai.2022.105075.
  • D. Simon, Evolutionary optimization algorithms. John Wiley & Sons, 2013.
  • T. H. Kim, I. Maruta, and T. Sugie, A simple and efficient constrained particle swarm optimization and its application to engineering design problems. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 224(2), 389-400, 2010. https://doi.org/ 10.1243/09544062JMES1732.
  • R. Moeini and M. H. Afshar, Layout and size optimization of sanitary sewer network using intelligent ants. Advances in Engineering Software 51,49–62, 2012. https://doi.org/ 10.1016/j.advengsoft.2012.05.003.
  • R. Moeini and M. H. Afshar, Arc based ant colony optimization algorithm for optimal design of gravitational sewer networks. Ain Shams Engineering Journal 8, 207–223, 2017. https://doi.org/ 10.1016/j.asej.2016.03.003.
  • M. Mansouri, M. Khanjani, Optimization of sewer networks using nonlinear programming. J Water Wastewater, 10(2), 20-30,1999.
  • W. H. Hassan, M. H. Jassem, and S. S. Mohammed, A GA-HP model for the optimal design of sewer networks. Water Resources Management 32:865-879, 2018. https://doi.org/10.1007/s11269-017-1843-y.
There are 34 citations in total.

Details

Primary Language Turkish
Subjects Water Resources Engineering, Water Resources and Water Structures
Journal Section Research Articles
Authors

Mustafa Erkan Turan 0000-0003-2501-2481

Tülin Çetin 0000-0002-1511-7338

Mümin Emre Şenol 0000-0002-2105-6041

Early Pub Date November 23, 2023
Publication Date January 15, 2024
Submission Date June 23, 2023
Acceptance Date November 9, 2023
Published in Issue Year 2024 Volume: 13 Issue: 1

Cite

APA Turan, M. E., Çetin, T., & Şenol, M. E. (2024). Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(1), 139-148. https://doi.org/10.28948/ngumuh.1318989
AMA Turan ME, Çetin T, Şenol ME. Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması. NOHU J. Eng. Sci. January 2024;13(1):139-148. doi:10.28948/ngumuh.1318989
Chicago Turan, Mustafa Erkan, Tülin Çetin, and Mümin Emre Şenol. “Kanalizasyon Optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13, no. 1 (January 2024): 139-48. https://doi.org/10.28948/ngumuh.1318989.
EndNote Turan ME, Çetin T, Şenol ME (January 1, 2024) Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13 1 139–148.
IEEE M. E. Turan, T. Çetin, and M. E. Şenol, “Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması”, NOHU J. Eng. Sci., vol. 13, no. 1, pp. 139–148, 2024, doi: 10.28948/ngumuh.1318989.
ISNAD Turan, Mustafa Erkan et al. “Kanalizasyon Optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13/1 (January 2024), 139-148. https://doi.org/10.28948/ngumuh.1318989.
JAMA Turan ME, Çetin T, Şenol ME. Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması. NOHU J. Eng. Sci. 2024;13:139–148.
MLA Turan, Mustafa Erkan et al. “Kanalizasyon Optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, vol. 13, no. 1, 2024, pp. 139-48, doi:10.28948/ngumuh.1318989.
Vancouver Turan ME, Çetin T, Şenol ME. Kanalizasyon optimizasyonu için kısıt yönetimi mekanizmalarının karşılaştırılması. NOHU J. Eng. Sci. 2024;13(1):139-48.

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