[1. Alijla B O, Wong, L.-P., Lim, C.P., Khader, A.T. and Al-Betar, M.A. (2014) A modified intelligent water drops algorithm and its application to optimization problems. Expert Systems with Applications, 41(15), 6555–6569. DOI: 10.1016/j.eswa.2014.05.010.]Open DOISearch in Google Scholar
[2. Alijla B O, Wong, L.-P., Lim, C.P., Khader, A.T. and Al-Betar, M.A. (2015) An ensemble of intelligent water drop algorithms and its application to optimization problems. Information Sciences, 325, 175–189. DOI: 10.1016/j.ins.2015.07.023.]Open DOISearch in Google Scholar
[3. Chang, T.S., Wan, Y.W. and Ooi, W.T. (2009) A stochastic dynamic traveling salesman problem with hard time windows. European Journal of Operational Research, 198(3), 748–759. DOI: 10.1016/j.ejor.2008.10.012.]Open DOISearch in Google Scholar
[4. Changdar, C., Mahapatra, G.S. and Pal, R.K. (2014) An efficient genetic algorithm for multi-objective solid travelling salesman problem under fuzziness. Swarm and Evolutionary Computation, 15, 27–37. DOI: 10.1016/j.swevo.2013.11.001.]Open DOISearch in Google Scholar
[5. Çela, E., Deineko, V. and Woeginger, G. J. (2012) The x-and-y-axes travelling salesman problem. European Journal of Operational Research, 223(2), 333–345. DOI: 10.1016/j.ejor.2012.06.036.]Open DOISearch in Google Scholar
[6. Colorni, A., Dorigo, M., Maniezzo, V. and Trubian, M. (1994) Ant system for job-shop scheduling. Belgian Journal of Operations Research, Statistics and Computer Science, 34(1), 39–53.]Search in Google Scholar
[7. Dantzig, G., Fulkerson, R. and Johnson, S. (1954) Solution of a large-scale traveling salesman problem. Journal of the Operations Research Society of America, 2(4), 393–410.]Search in Google Scholar
[8. Dorigo M and Di Caro G. (1999) Ant colony optimization: A new meta-heuristic. In: Proceedings of the 1999 Congress on Evolutionary Computation-CEC 99 (Cat. No. 99TH8406), 06–09 July 1999, Washington, DC, USA: IEEE, 1470–1477.]Search in Google Scholar
[9. Eberhart, R. C. and Shi, Y. (2001) Particle swarm optimization: Developments, applications and resources. In: Proceedings of the 2001 Congress on Evolutionary Computation (Cat. No.01TH8546), 27–30 May, Seoul, Korea (South): IEEE, 81–86.]Search in Google Scholar
[10. Eckenrode, R. T. (1965) Weighting multiple criteria. Management Science, 12(3), 180–192.]Search in Google Scholar
[11. Erdoǧan, G., Cordeau, J.-F. and Laporte, G. (2010) The attractive traveling salesman problem. European Journal of Operational Research, 203(1), 59–69. DOI: 10.1016/j.ejor.2009.06.029.]Open DOISearch in Google Scholar
[12. Focacci, F., Lodi, A. and Milano, M. (2002) A hybrid exact algorithm for the TSPTW. INFORMS Journal on Computing, 14(4), 403–417. DOI: 10.1287/ijoc.14.4.403.2827.]Open DOISearch in Google Scholar
[13. Holland, J. H. (1975) Adaptation in neural and artificial system. Cambridge: University of Michigan Press.]Search in Google Scholar
[14. Karaboga, D. (2005) An idea based on honey bee swarm for numerical optimization. Kayseri: Erciyes University Press.]Search in Google Scholar
[15. Liu, B. (2009) Some research problems in uncertainty theory. Journal of Uncertain Systems, 3(1): 3–10.]Search in Google Scholar
[16. Liu, B. (2007) Uncertainty theory (2nd ed.), Berlin: Springer-Verlag.]Search in Google Scholar
[17. Liu, B. (2010) Uncertainty theory: A branch of mathematics for modeling human uncertainty (2nd ed.). Berlin: Springer-Verlag.]Search in Google Scholar
[18. Liu, B. (2012) Why is there a need for uncertainty theory? Journal of Uncertain Systems, 6(1), 3–10.]Search in Google Scholar
[19. Liu, B. (2015) Uncertainty theory (5th ed.). Beijing: Uncertainty Theory Laboratory.]Search in Google Scholar
[20. Liu, Y. H. (2010) Different initial solution generators in genetic algorithms for solving the probabilistic traveling salesman problem. Applied Mathematics and Computation, 216(1), 125–137.DOI: 10.1016/j.amc.2010.01.021.]Open DOISearch in Google Scholar
[21. Majumdar, J. and Bhunia, A. K. (2011) Genetic algorithm for asymmetric traveling salesman problem with imprecise travel times. Journal of Computational and Applied Mathematics, 235(9), 3063–3078. DOI: 10.1016/j.cam.2010.12.027.]Open DOISearch in Google Scholar
[22. Majumder, S, Saha, B., Anand, P., Kar, S. and Pal, T. (2018b) Uncertainty based genetic algorithm with varying population for random fuzzy maximum flow problem. Expert Systems, 35(4), e12264. DOI: 10.1111/exsy.12264]Open DOISearch in Google Scholar
[23. Majumder, S., Kar, S., and Pal, T. (2019) Uncertain multi-objective Chinese postman problem. Soft Computing, 23(22), 11557–11572. DOI: 10.11007/s00500-018-03697-3]Open DOISearch in Google Scholar
[24. Majumder, S., Barma, P.S., Biswas, B., Banerjee, P., Kumar B., Kar, S., and Ziemba, P. (2022) On multi-objective minimum spanning tree problem under uncertain paradigm. Symmetry, 14(1), 106. DOI: 10.3390/sym14010106]Open DOISearch in Google Scholar
[25. Mestria, M., Ochi, L. S. and Martins, S. L. (2013) GRASP with path relinking for the symmetric Euclidean clustered traveling salesman problem. Computers and Operations Research, 40(12), 3218–3229. DOI: 10.1016/j.cor.2012.10.001.]Open DOISearch in Google Scholar
[26. Moon, C., Ki, J., Choi, G., and Seo, Y. (2002) An efficient genetic algorithm for the traveling salesman problem with precedence constraints. European Journal of Operational Research, 140(3), 606–617. DOI: 10.1016/S0377-2217(01)00227-2.]Open DOISearch in Google Scholar
[27. Nagalakshmi, P., Harish, Y., Kranthi Kumar, R. and Chakravarthi, J. (2011) Combined economic and emission dispatch using intelligent water drops-continuous optimization algorithm. In: International conference on Recent Advancements in Electrical, Electronics and Control Engineering (ICONRAEeCE), 15–17 December 2011; Sivakasi, India: IEEE, 168–173.]Search in Google Scholar
[28. Niu, S. H., Ong, S. K. and Nee, A. Y. C. (2011) An improved intelligent water drops algorithm for achieving optimal job-shop scheduling solutions. International Journal of Production Research, 50(15), 4192–4205. DOI: 10.1080/00207543.2011.600346.]Open DOISearch in Google Scholar
[29. Noferesti, S. and Shah-Hosseini. H. (2012) A hybrid algorithm for solving steiner tree problem. International Journal of Computer Applications, 41(5), 14–20. DOI: 10.5120/5536-7584]Open DOISearch in Google Scholar
[30. Rakke, J. G., Christiansen, M., Fagerholt, K. and Laportei, G. (2012). The traveling salesman problem with draft limits. Computers and Operations Research, 39(9), 2161–2167. DOI: 10.1016/j.cor.2011.10.025.]Open DOISearch in Google Scholar
[31. Rego, C., Gamboa, D., Glover, F. and Osterman, C. (2011) Traveling salesman problem heuristics: Leading methods, implementations and latest advances. European Journal of Operational Research, 211(3), 427–441. DOI: 10.1016/j.ejor.2010.09.010.]Open DOISearch in Google Scholar
[32. Samanlioglu, F., Ferrell, W.G. and Kurz, M.E. (2008) A memetic random-key genetic algorithm for a symmetric multi-objective traveling salesman problem. Computers & Industrial Engineering, 55(2), 439–449. DOI: 10.1016/j.cie.2008.01.005.]Open DOISearch in Google Scholar
[33. Shah-Hosseini, H. (2007) Problem solving by intelligent water drops. In: The 2007 Congress on Evolutionary Computation (CEC 2007), 25–28 September 2007; Singapore: IEEE, 3226–3231.]Search in Google Scholar
[34. Shah-Hosseini, H. (2008) Intelligent water drops algorithm: A new optimization method for solving the multiple knapsack problem. International Journal of Intelligent Computing and Cybernetics, 1(2), 193–212. DOI: 10.1108/17563780810874717.]Open DOISearch in Google Scholar
[35. Shah-Hosseini, H. (2009a) Optimization with the nature-inspired intelligent water drops algorithm. In: Santos W. (eds.) Evolutionary Computations. Federal University of Pernambuco, Brazil, 297–320.]Search in Google Scholar
[36. Shah-Hosseini, H. (2009b) The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm. International Journal of Bio-Inspired Computation, 1(2), 71–79. DOI: 10.1504/IJBIC.2009.022775.]Open DOISearch in Google Scholar
[37. Wang, Z., Guo, J., Zheng, M. and Yang, Y. (2015a) A new approach for uncertain multi-objective programming problem based on 𝒫E principle. Journal of Industrial and Management Optimization, 11(1), 13–26. DOI: 10.3934/jimo.2015.11.13.]Open DOISearch in Google Scholar
[38. Wang, Z., Guo, J., Zheng, M. and Wang, Y. (2015b) Uncertain multi-objective traveling salesman problem. European Journal of Operational Research, 241(2), 478–489. DOI: 10.1016/j.ejor.2014.09.012.]Open DOISearch in Google Scholar
[39. Zhou, J., Chen, L. and Wang, K. (2015) Path optimality conditions for minimum spanning tree problem with Uncertain edge weights. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 23(1), 49–71. DOI: 10.1142/S0218488515500038.]Open DOISearch in Google Scholar
