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COMPARING THE SOLUTION PERFORMANCES OF THE HEURISTIC AND METAHEURISTIC ALGORITHMS IN TRAVELLING SALESMAN PROBLEM

Yıl 2019, Cilt: 19 Sayı: 4, 911 - 932, 31.12.2019
https://doi.org/10.11616/basbed.v19i51339.558208

Öz

The Traveling Salesman Problem is the problem
of identifying a route that will enable a salesman to visit all the cities only
once in the list where the cities are located, to start and to return the city
where he lives by traveling the shortest distance. In this study, the solution
performances of a series of heuristic and metaheuristic methods in Travelling Salesman
Problem is compared. Within the scope of the study, the nearest neighbor and
2-Opt methods were used as heuristic methods, and the Ant Colony Optimization,
Tabu Search, Simulated Annealing and Genetic Algorithm methods were used as
metaheuristic methods. As a result of the experiments conducted with 16 data
sets, it was determined that the integrated method consisting of the Nearest
Neighbor and 2-Opt heuristics provide the best solutions in terms of average
solution values and times.

Kaynakça

  • Ahmadi, A., El Bouanani, F. ve Ben-Azza, H. (2014), Four Parallel Decoding Schemas of Product BlockCodes,Transactions on Networks and Communications, 2(3), s.49-69.
  • Alshamsi, A. ve Diabat, A. (2017), A Genetic Algorithm for Reverse Logistics Network Design: A Case Study From the GCC, Journal of Cleaner Production, 151, s.652-669.
  • Antosiewicz, M., Koloch, G. ve Kamiński, B. (2013), Choice of best possible Metaheuristic Algorithm for the Travelling Salesman Problem with Limited Computational Time: Quality, Uncertainty and Speed, Journal of Theoretical and Applied Computer Science, 7(1), s.46-55.
  • Archetti, C., Speranza, M. G. ve Hertz, A. (2006), A Tabu Search Algorithm for the Split Delivery Vehicle Routing Problem, Transportation Science, 40(1), s.64-73.
  • Aycan, E. ve Ayav, T. (2009), Solving the Course Scheduling Problem Using Simulated Annealing, 2009 IEEE International Advance Computing Conference, Patiala, India.
  • Barbarosoglu, G. ve Özgur, D. (1999), A Tabu Search Algorithm for the Vehicle Routing Problem, Computers&Operations Research, 26(3), s.255-270.
  • Bilge, Ü., Kıraç, F., Kurtulan, M. ve Pekgün, P. (2004), A Tabu Search Algorithm for Parallel Machine Total Tardiness Problem, Computers & Operations Research, 31(3), s.397-414.
  • Bouzidi, S., Riffi, M. E. ve Bouzidi, A. (2017), Comparative analysis of Three Metaheuristics for Solving the Travelling Salesman Problem, Transactions on Machine Learning and Artificial Intelligence, 5(4), s.395-402.
  • Burke E.K., Cowling P.I. ve Keuthen R. (1999), New Models and Heuristics for Component Placement in Printed Circuit Board Assembly, 1999 International Conference on Information Intelligence and Systems, Bethesda, Maryland.
  • Chowdhury, A., Ghosh, A., Sinha, S., Das, S. ve Ghosh, A. (2013), A Novel Genetic Algorithm to Solve Travelling Salesman Problem and Blocking Flow Shop Scheduling Problem, International Journal of Bio-Inspired Computation, 5(5), s.303-314.
  • Correia, M. H., Oliveira, J. F. ve Ferreira, J. S. (2000), Cylinder Packing by Simulated Annealing, Pesquisa Operacional, 20(2): 269-286.
  • Cunha, M. D. C. ve Sousa, J. (1999), Water Distribution Network Design Optimization: Simulated Annealing Approach, Journal of Water Resources Planning and Management, 125(4), s.15-221.
  • Dantzig, G., Fulkerson, R. ve Johnson, S. (1954), Solution of a Large-Scale Traveling-Salesman Problem, Journal of the Operations Research Society of America, 2(4), s.393-410.
  • Deng, Y., Liu, Y. ve Zhou, D. (2015), An Improved Genetic Algorithm -with Initial Population Strategy for Symmetric TSP, Mathematical Problems in Engineering, 2015, s.1-6.
  • Dikmen, H., Dikmen, H., Elbir, A., Eksi, Z. ve Çelik, F. (2014), Gezgin Satıcı Probleminin Karınca Kolonisi ve Genetik Algoritmalarla Eniyilemesi ve Karşılaştırılması, Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 18(1), s.8-13.
  • Ding, Y. ve Fu, X. (2016), Kernel-Based Fuzzy C-Means Clustering Algorithm Based on Genetic Algorithm, Neurocomputing, 188, s.33-238.
  • Dorigo, M., Maniezzo, V. ve Colorni, A. (1991), Ant System: An Autocatalytic Optimizing Process, Politecnico di Milano: https://pdfs.semanticscholar.org/9649/211474dcfc3a9fd75e5208ffd21d9dcb9794.pdf, ErişimTarihi: (18.12.2018)
  • Dorigo, M. ve Gambardella, L.M. (1997), Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transactions on evolutionary computation, 1(1), s.53-66.
  • Dorigo, M. ve Stützle, T. (2019), Ant Colony Optimization: Overview and Recent Advances (Eds: M. Gendreau, J.-Y. Potvin), Handbook of Metaheuristics, s.311-351, Springer, Cham.
  • Fiechter, C. N. (1994), A Parallel Tabu Search Algorithm for Large Traveling Salesman Problems, Discrete Applied Mathematics, 51(3), s.243-267.
  • Freisleben, B. ve Merz, P. (1996), A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems, IEEE International Conference on Evolutionary Computation, Nagoya.
  • Fuellerer, G., Doerner, K.F., Hartl, R.F. ve Iori, M. (2009), Ant Colony Optimization for the Two-Dimensional Loading Vehicle Routing Problem, Computers & Operations Research, 36(3), s.655-673.
  • Gambardella, L. M. ve Dorigo, M. (2000), An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem, INFORMS Journal on Computing, 12(3), s.237-255.
  • Gendreau M., Laporte G. ve Semet F. (1998), A Tabu Search Heuristic for the Undirected Selective Travelling Salesman Problem, European Journal of Operational Research, 106 (2-3), s.539-545.
  • Gendreau, M., Iori, M., Laporte, G. ve Martello, S. (2006), A Tabu Search Algorithm for a Routing And Container Loading Problem”, Transportation Science, 40(3), s.342-350.
  • Gilli, M., Maringer, D. ve Schumann, E. (2011), Numerical Methods and Optimization in Finance. San Diago: Academic Press.
  • Glover, F. ve Laguna, M. (1989), Tabu Search-Part I, ORSA Journal on Computing, 1 (3), s.190-206.
  • Glover, F. ve Laguna, M. (1997),Tabu Search (First Edition). Massachusetts: Kluwer Academic Publishers.
  • Grabowski, J. ve Wodecki, M. (2004), A Very Fast Tabu Search Algorithm for the Permutation Flow Shop Problem with Makespan Criterion, Computers & Operations Research, 31(11), s.1891-1909.
  • Gupta, D. (2013), Solving tsp using various meta-heuristic algorithms, International Journal of Recent Contributions from Engineering, Science & IT (iJES), 1(2), s.22-26.
  • Gupta, S. ve Panwar, P. (2013), Solving Travelling Salesman Problem Using Genetic Algorithm, International Journal of Advanced Research in Computer Science and Software Engineering, 3(6), s.376-380.
  • Halim, A. H. ve Ismail, I. (2019), Combinatorial optimization: comparison of heuristic algorithms in travelling salesman problem, Archives of Computational Methods in Engineering, 26(2), s.367-380.
  • Hiassat, A., Diabat, A. ve Rahwan, I. (2017), A Genetic Algorithm Approach for Location-Inventory-Routing Problem with Perishable Products, Journal of manufacturing systems, 42, s.93-103.
  • Hoffman K.L. ve Padberg M. (1993), Solving Airline Crew Scheduling Problems by Branch-and-Cut, Management Science, 39(6), s.657-682.
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SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI

Yıl 2019, Cilt: 19 Sayı: 4, 911 - 932, 31.12.2019
https://doi.org/10.11616/basbed.v19i51339.558208

Öz

Bu çalışmanın amacı, sezgisel ve metasezgisel yöntemlerin Gezgin Satıcı
Problemi çözüm performanslarının çözüm değeri ve süresi bakımından değerlendirilmesidir.
Çalışma kapsamında, sezgisel yöntem olarak bütünleşik En Yakın Komşu (EYK) ve
2-Opt sezgiseli, metasezgisel yöntem olarak ise karınca kolonisi optimizasyon,
tabu arama, benzetilmiş tavlama ve genetik algoritma yöntemleri kullanılmıştır.
16 adet veri seti ile yapılan deneyler, ortalama çözüm değerleri ve süreleri
bakımından EYK+2-Opt bütünleşik yönteminin en iyi çözümleri sağladığını
göstermiştir. Sonuç olarak, EYK+2-Opt yönteminin Gezgin Satıcı Probleminin
çözümünde hızlı ve etkin çözümler üretebilen kullanışlı bir yöntem olduğu ortaya
konmuştur.  

Kaynakça

  • Ahmadi, A., El Bouanani, F. ve Ben-Azza, H. (2014), Four Parallel Decoding Schemas of Product BlockCodes,Transactions on Networks and Communications, 2(3), s.49-69.
  • Alshamsi, A. ve Diabat, A. (2017), A Genetic Algorithm for Reverse Logistics Network Design: A Case Study From the GCC, Journal of Cleaner Production, 151, s.652-669.
  • Antosiewicz, M., Koloch, G. ve Kamiński, B. (2013), Choice of best possible Metaheuristic Algorithm for the Travelling Salesman Problem with Limited Computational Time: Quality, Uncertainty and Speed, Journal of Theoretical and Applied Computer Science, 7(1), s.46-55.
  • Archetti, C., Speranza, M. G. ve Hertz, A. (2006), A Tabu Search Algorithm for the Split Delivery Vehicle Routing Problem, Transportation Science, 40(1), s.64-73.
  • Aycan, E. ve Ayav, T. (2009), Solving the Course Scheduling Problem Using Simulated Annealing, 2009 IEEE International Advance Computing Conference, Patiala, India.
  • Barbarosoglu, G. ve Özgur, D. (1999), A Tabu Search Algorithm for the Vehicle Routing Problem, Computers&Operations Research, 26(3), s.255-270.
  • Bilge, Ü., Kıraç, F., Kurtulan, M. ve Pekgün, P. (2004), A Tabu Search Algorithm for Parallel Machine Total Tardiness Problem, Computers & Operations Research, 31(3), s.397-414.
  • Bouzidi, S., Riffi, M. E. ve Bouzidi, A. (2017), Comparative analysis of Three Metaheuristics for Solving the Travelling Salesman Problem, Transactions on Machine Learning and Artificial Intelligence, 5(4), s.395-402.
  • Burke E.K., Cowling P.I. ve Keuthen R. (1999), New Models and Heuristics for Component Placement in Printed Circuit Board Assembly, 1999 International Conference on Information Intelligence and Systems, Bethesda, Maryland.
  • Chowdhury, A., Ghosh, A., Sinha, S., Das, S. ve Ghosh, A. (2013), A Novel Genetic Algorithm to Solve Travelling Salesman Problem and Blocking Flow Shop Scheduling Problem, International Journal of Bio-Inspired Computation, 5(5), s.303-314.
  • Correia, M. H., Oliveira, J. F. ve Ferreira, J. S. (2000), Cylinder Packing by Simulated Annealing, Pesquisa Operacional, 20(2): 269-286.
  • Cunha, M. D. C. ve Sousa, J. (1999), Water Distribution Network Design Optimization: Simulated Annealing Approach, Journal of Water Resources Planning and Management, 125(4), s.15-221.
  • Dantzig, G., Fulkerson, R. ve Johnson, S. (1954), Solution of a Large-Scale Traveling-Salesman Problem, Journal of the Operations Research Society of America, 2(4), s.393-410.
  • Deng, Y., Liu, Y. ve Zhou, D. (2015), An Improved Genetic Algorithm -with Initial Population Strategy for Symmetric TSP, Mathematical Problems in Engineering, 2015, s.1-6.
  • Dikmen, H., Dikmen, H., Elbir, A., Eksi, Z. ve Çelik, F. (2014), Gezgin Satıcı Probleminin Karınca Kolonisi ve Genetik Algoritmalarla Eniyilemesi ve Karşılaştırılması, Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 18(1), s.8-13.
  • Ding, Y. ve Fu, X. (2016), Kernel-Based Fuzzy C-Means Clustering Algorithm Based on Genetic Algorithm, Neurocomputing, 188, s.33-238.
  • Dorigo, M., Maniezzo, V. ve Colorni, A. (1991), Ant System: An Autocatalytic Optimizing Process, Politecnico di Milano: https://pdfs.semanticscholar.org/9649/211474dcfc3a9fd75e5208ffd21d9dcb9794.pdf, ErişimTarihi: (18.12.2018)
  • Dorigo, M. ve Gambardella, L.M. (1997), Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transactions on evolutionary computation, 1(1), s.53-66.
  • Dorigo, M. ve Stützle, T. (2019), Ant Colony Optimization: Overview and Recent Advances (Eds: M. Gendreau, J.-Y. Potvin), Handbook of Metaheuristics, s.311-351, Springer, Cham.
  • Fiechter, C. N. (1994), A Parallel Tabu Search Algorithm for Large Traveling Salesman Problems, Discrete Applied Mathematics, 51(3), s.243-267.
  • Freisleben, B. ve Merz, P. (1996), A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems, IEEE International Conference on Evolutionary Computation, Nagoya.
  • Fuellerer, G., Doerner, K.F., Hartl, R.F. ve Iori, M. (2009), Ant Colony Optimization for the Two-Dimensional Loading Vehicle Routing Problem, Computers & Operations Research, 36(3), s.655-673.
  • Gambardella, L. M. ve Dorigo, M. (2000), An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem, INFORMS Journal on Computing, 12(3), s.237-255.
  • Gendreau M., Laporte G. ve Semet F. (1998), A Tabu Search Heuristic for the Undirected Selective Travelling Salesman Problem, European Journal of Operational Research, 106 (2-3), s.539-545.
  • Gendreau, M., Iori, M., Laporte, G. ve Martello, S. (2006), A Tabu Search Algorithm for a Routing And Container Loading Problem”, Transportation Science, 40(3), s.342-350.
  • Gilli, M., Maringer, D. ve Schumann, E. (2011), Numerical Methods and Optimization in Finance. San Diago: Academic Press.
  • Glover, F. ve Laguna, M. (1989), Tabu Search-Part I, ORSA Journal on Computing, 1 (3), s.190-206.
  • Glover, F. ve Laguna, M. (1997),Tabu Search (First Edition). Massachusetts: Kluwer Academic Publishers.
  • Grabowski, J. ve Wodecki, M. (2004), A Very Fast Tabu Search Algorithm for the Permutation Flow Shop Problem with Makespan Criterion, Computers & Operations Research, 31(11), s.1891-1909.
  • Gupta, D. (2013), Solving tsp using various meta-heuristic algorithms, International Journal of Recent Contributions from Engineering, Science & IT (iJES), 1(2), s.22-26.
  • Gupta, S. ve Panwar, P. (2013), Solving Travelling Salesman Problem Using Genetic Algorithm, International Journal of Advanced Research in Computer Science and Software Engineering, 3(6), s.376-380.
  • Halim, A. H. ve Ismail, I. (2019), Combinatorial optimization: comparison of heuristic algorithms in travelling salesman problem, Archives of Computational Methods in Engineering, 26(2), s.367-380.
  • Hiassat, A., Diabat, A. ve Rahwan, I. (2017), A Genetic Algorithm Approach for Location-Inventory-Routing Problem with Perishable Products, Journal of manufacturing systems, 42, s.93-103.
  • Hoffman K.L. ve Padberg M. (1993), Solving Airline Crew Scheduling Problems by Branch-and-Cut, Management Science, 39(6), s.657-682.
  • İnak, N., Tokat, S. ve Karagül, K. (2018),Alt Sınır Temeline Dayalı Ağırlıklı Tavlama Yöntemi ile Kutulama Probleminin Çözümü, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 5(3), s.549-567.
  • Johnson, D. S., Aragon, C. R., McGeoch, L. A. ve Schevon, C. (1989), Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning, Operations research, 37(6), s.865-892.
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  • Mohammed, M.A., Ghani, M.K.A., Hamed, R.I., Mostafa, S.A., Ahmad, M.S. ve Ibrahim, D.A. (2017), Solving Vehicle Routing Problem by Using Improved Genetic Algorithm for Optimal Solution, Journal of Computational Science, 21, s.255-262.
  • Nowicki, E. ve Smutnicki, C. (1996), A Fast Taboo Search Algorithm for the Job Shop Problem, Management Science, 42(6), s.797-813.
  • Odili, J.B., Kahar, M.N.M., Noraziah, A., Zarina, M. ve Haq, R. U. (2017), Performance Analysis of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management, Intelligent Automation&Soft Computing, 1-11.doi:10.1080/10798587.2017.1334370
  • Otero, F. E., Freitas, A. A. ve Johnson, C. G. (2008), cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes, International Conference on Ant Colony Optimization and Swarm Intelligence, Brussels.
  • Özcan, U. ve Toklu, B. (2009), Balancing of Mixed-Model Two-Sided Assembly Lines, Computers&Industrial Engineering, 57(1), s.217-227.
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Toplam 87 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Yusuf Şahin 0000-0002-3862-6485

Yayımlanma Tarihi 31 Aralık 2019
Gönderilme Tarihi 26 Nisan 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 19 Sayı: 4

Kaynak Göster

APA Şahin, Y. (2019). SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 19(4), 911-932. https://doi.org/10.11616/basbed.v19i51339.558208
AMA Şahin Y. SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI. ASBİ. Aralık 2019;19(4):911-932. doi:10.11616/basbed.v19i51339.558208
Chicago Şahin, Yusuf. “SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI”. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 19, sy. 4 (Aralık 2019): 911-32. https://doi.org/10.11616/basbed.v19i51339.558208.
EndNote Şahin Y (01 Aralık 2019) SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 19 4 911–932.
IEEE Y. Şahin, “SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI”, ASBİ, c. 19, sy. 4, ss. 911–932, 2019, doi: 10.11616/basbed.v19i51339.558208.
ISNAD Şahin, Yusuf. “SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI”. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 19/4 (Aralık 2019), 911-932. https://doi.org/10.11616/basbed.v19i51339.558208.
JAMA Şahin Y. SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI. ASBİ. 2019;19:911–932.
MLA Şahin, Yusuf. “SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI”. Bolu Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, c. 19, sy. 4, 2019, ss. 911-32, doi:10.11616/basbed.v19i51339.558208.
Vancouver Şahin Y. SEZGİSEL VE METASEZGİSEL YÖNTEMLERİN GEZGİN SATICI PROBLEMİ ÇÖZÜM PERFORMANSLARININ KIYASLANMASI. ASBİ. 2019;19(4):911-32.

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