Abstract
In this paper, a Rough Genetic Algorithm (RGA) is proposed to solve constrained solid travelling salesman problems (CSTSPs) in crisp and bi-fuzzy coefficients. In the proposed RGA, we developed a ‘rough set based selection’ (7-point scale) technique and ‘comparison crossover’ with new generation dependent mutation. A solid travelling salesman problem (STSP) is a tavelling salesman problem (TSP) in which, at each station, there are a number of conveyances available to travel to another station. The costs and risk/discomforts factors are in the form of crisp, bi-fuzzy in nature. In this paper, CSTSPs are illustrated numerically by some standard test data from TSPLIB using RGA. In each environment, some statistical significance studies due to different risk/discomfort factors and other system parameters are presented.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Lawler, E.L., Lenstra, J.K., Rinnooy Kan, A.H.G.: The TSP: G.E. Re Guided Tour of Combinatorial Optimization. Wiley, New York (1985)
Focacci, F., Lodi, A., Milano, M.: A hybrid exact algorithm for the TSPTW. Inf. J. Comput. 14(4), 403–417 (2002)
Chang, T., Wan, Y., Tooi, W.: A stochastic dynamic travelling salesman problem with hard time windows. Eur. J. Oper. Res. 198(3), 748–759 (2009)
Petersen, H.L., Madsen, O.B.G.: The double travelling salesman problem with multiple stack—formulation heuristic solution approaches. Eur. J. Oper. Res. 198, 339–347 (2009)
Majumder, S.K., Bhunia, A.K.: Genetic algorithm for asymmetric traveling salesman problem with imprecise travel times. J. Comput. Appl. Math. 235(9), 3063–3078 (2011)
Moon, C., Ki, J., Choi, G., Seo, Y.: An efficient genetic algorithm for the TSP with precedence constraints. EJOR 140, 606–617 (2002)
Maity, S., Roy, A., Maiti, M.: A modified genetic algorithm for solving uncertain CSTSP. Comput. Ind. Eng. 83, 273–296 (2015)
Xu, J., Zhou, X.: Fuzzy-Like Multiple Objective Decision Making, Studies in Fuzziness and Soft Computing. Springer, New York (2011)
Ni, H., Wang, Y.: Stack index tracking by pareto efficient GA. Appl. Soft Comput. 13(12), 4519–4535 (2013)
Ursani, Z., Essam, D., Cornforth, D., Stocker, R.: Localized genetic algorithm for vehicle routing problem with time windows. Appl. Soft Comput. 11(8), 5375–5390 (2011)
Neungmatcha, W., Sethanan, K., Gen, M., Theerakulpisut, S.: Adaptive genetic algorithm for solving sugarcane loading stations with multi-facility services problem. Comput. Electron. Agric. 98(10), 85–99 (2013)
Huang, K.Y.: An enhance classification method comparing a GA, rough set theory and modified PBMF-index function. Appl. Soft Comput. 12(10), 46–63 (2012)
Enigin, O., Ceran, G., Yilmaz, M.K.: An efficient GA for hybrid flow shop scheduling with multiprocessor task problem. Appl. Soft Comput. 11(3), 3056–3065 (2011)
Last, M., Eyal, S.: A fuzzy-based lifetime extension of genetic algorithms. Fuzzy Sets Syst. 149, 131–147 (2005)
Roy, A., Kar, S., Maiti, M.: A production inventory model with stock dependent..: a fuzzy genetic algorithm with varying population size approach. Comput. Ind. Eng. 57, 1324–1335 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Maity, S., Roy, A., Maiti, M. (2016). Constrained Solid Travelling Salesman Problem Solving by Rough GA Under Bi-Fuzzy Coefficients. In: Das, S., Pal, T., Kar, S., Satapathy, S., Mandal, J. (eds) Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015. Advances in Intelligent Systems and Computing, vol 404. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2695-6_36
Download citation
DOI: https://doi.org/10.1007/978-81-322-2695-6_36
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2693-2
Online ISBN: 978-81-322-2695-6
eBook Packages: EngineeringEngineering (R0)