1. Lawler, E.L., Lenstra, J.K., Rinnooy Kan, A.H.G., and Shmoys, D.B., The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization, John Wiley & Sons (1985). 2. Gutin, G. and Punnen, A.P., The Traveling Salesman Problem and Its Variations, Springer (2006). 3. Cook, W., In Pursuit of the Traveling Salesman: Mathematics at the Limits of Computation, Princeton University Press (2011). 4. Toth, P. and Vigo, D., The Vehicle Routing Problem, Philadelphia: SIAM (2001). 5. Oliveira, H.C.B. and Vasconcelos, G.C. A hybrid search method for the vehicle routing problem with time windows", Annals of Operations Research, 180(1), pp. 125-144 (2008). 6. Pillac, V., Gendreau, M., Gu_eret, C., and Medaglia, A.L. A review of dynamic vehicle routing problems", European Journal of Operational Research, 225(1), pp. 1-11 (2013). 7. Beltrami, E.J. and Bodin, L.D. Networks and vehicle routing for municipal waste collection", Networks, 4(1), pp. 65-94 (1974). 8. Francis, P.M., Smilowitz, K.R., and Tzur, M. The period vehicle routing problem and its extensions", (book series) Operations Research/Computer Science Interfaces, 43, pp. 73-102 (2008). 9. Mourgaya, M. and Vanderbeck, F. The periodic vehicle routing problem: classi_cation and heuristic", RAIRO - Operations Research, 40(2), pp. 169-194 (2006). 10. Nguyen, P.K., Crainic, T.G., and Toulouse, M. Hybrid generational genetic algorithm for the periodic vehicle routing problem with time windows", Journal of Heuristics, 20(4), pp. 383-416 (2014). 11. Michallet, J., Prins, C., Amodeo, L., Yalaoui, F., and Vitry, G. Multi-start iterated local search for the periodic vehicle routing problem with time windows and time spread constraints on services", Computers & Operations Research, 41, pp. 196-207 (2014). 12. Ko_c, C_ . A uni_ed-adaptive large neighborhood search metaheuristic for periodic location-routing problems", Transportation Research Part C, 68, pp. 265-284 (2016). 13. Lim, W.C.E., Kanagaraj, G., and Ponnambalam, S.G. A hybrid cuckoo search-genetic algorithm for holemaking sequence optimization", Journal of Intelligent Manufacturing, 27(2), pp. 417-429 (2016). 14. Dalavi, A.M., Pawar, P.J., and Singh, T.P. Tool path planning of hole-making operations in ejector plate of injection mould using modi_ed shu_ed frog leaping algorithm", Journal of Computational Design and Engineering, 3, pp. 266-273 (2016). 15. Dalavi, A.M., Pawar, P.J., Singh, T.P., Warke, A.S., and Paliwal, P.D. Review on optimization of holemaking operations for injection mould using nontraditional algorithms", International Journal of Industrial Engineering and Management, 7(1), pp. 9-14 (2016). 16. Solimanpur, M., Foroughi, A., and Mohammadi, M. Optimum route selection in hole-making operations using a dynamic programming-based method", Cogent Engineering, 3, Article 1201991 (2016). http://dx.doi.org/10.1080/23311916.2016 .1201991 17. Garey, M.R. and Johnson, D.S., Computers and Intractability: A Guide to the Theory of NPCompleteness, Macmillan (1979). 18. Mirjalili, S. and Lewis, A. The whale optimization algorithm", Advances in Engineering Software, 95, pp. 51-67 (2016). 19. Li, Z., Mobin, M., and Keyser, T. Multi-objective and multi-stage reliability growth planning in early product development stage", IEEE Transaction on Reliability, 65, pp. 769-781 (2016). 20. Tavana, M., Li, Z., Mobin, M., Komaki, M., and Teymurian, E. Multi-objective design of control chart optimization using NSGA-III and MOPSO enhanced with DEA and TOPSIS", Expert System with Applications, 50, pp. 17-39 (2016). 21. Tavana, M., Kazemi, M.R., Vafadarnikjoo, A., and Mobin, M. An arti_cial immune algorithm for ergonomic product classi_cation using anthropometric measurements", Measurement, 94, pp. 621-629 (2016). 22. Weissman, I.L. and Cooper, M.D. How the immune system develops", Scienti_c American, 269, pp. 33-40 (1993). 23. Huang, S.J. Enhancement of thermal unit commitment using immune algorithms based optimization approaches", Electrical Power & Energy Systems, 21, pp. 245-252 (1999). 24. Hsieh, Y.C. and You, P.S. An e_ective immune based two-phase approach for the optimal reliabilityredundancy allocation problem", Applied Mathematics and Computation, 218, pp. 1297-1307 (2011). 25. Hsieh, Y.C. and You, P.S. An immune evolutionary approach for the label printing problem", International Journal of Computational Intelligence Systems, 7(3), pp. 515-523 (2014). 26. Michalewicz, Z., Genetic Algorithm + Data Structures = Evolution Programs, Springer-Verlag, New York (1994). 27. Kennedy, J. and Eberhart, R., Particle swarm optimization", Proceedings of IEEE International Conference on Neural Networks, IV, pp. 1942-1948 (1995). 28. Chen, W. and Zhang, J. A novel set-based particle swarm optimization method for discrete optimization problem", IEEE Transactions on Evolutionary Computation, 14(2), pp. 278-300 (2010). 29. Eberhart, R.C., Hu, X., and Shi, Y. Particle swarm with extended memory for multiobjective optimization", IEEE International Conference on Swarm Intelligence Symposium, pp. 193-197 (2003).