References
- Ai, T. J., and V. Kachitvichyanukul. 2009. A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Computers & Operations Research 36 (5):1693–702. doi:10.1016/j.cor.2008.04.003.
- Avci, M., and S. Topaloglu. 2015. An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries. Computers & Industrial Engineering 83:15–29. doi:10.1016/j.cie.2015.02.002.
- Baker, B. M., and M. A. Ayechew. 2003. A genetic algorithm for the vehicle routing problem. Computers & Operations Research 30 (5):787–800. doi:10.1016/S0305-0548(02)00051-5.
- Chen, S. M., A. Sarosh, and Y. F. Dong. 2012. Simulated annealing based artificial bee colony algorithm for global numerical optimization. Applied Mathematics and Computation 219 (8):3575–89.
- Dethloff, J. 2001. Vehicle routing and reverse logistics: The vehicle routing problem with simultaneous delivery and pick-up. OR Spektrum 23 (1):79–96. doi:10.1007/PL00013346.
- Dorigo, M., and G. Di Caro. 1999. Ant colony optimization: a new meta-heuristic. Proceedings of the IEEE 1999 Congress on Evolutionary Computation(Cat. No. 99TH8406) 2:1470–77.
- Dorigo, M., V. Maniezzo, and A. Colorni. 1991. Positive feedback as a search strategy.
- Dos Santos Coelho, L., and P. Alotto. 2011. Gaussian artificial bee colony algorithm approach applied to Loney’s solenoid benchmark problem. IEEE Transactions on Magnetics 47 (5):1326–29. doi:10.1109/TMAG.20.
- Fister, I., I. Fister, J. Brest, and V. Žumer. 2012. Memetic artificial bee colony algorithm for large-scale global optimization. IEEE Congress on Evolutionary Computation, CEC 2012 10–15. doi:10.1109/CEC.2012.6252938.
- Gajpal, Y., and P. Abad. 2009. An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup. Computers & Operations Research 36 (12):3215–23. doi:10.1016/j.cor.2009.02.017.
- Ghanem, W. A. H. M., and A. Jantan. 2018. Hybridizing artificial bee colony with monarch butterfly optimization for numerical optimization problems. Neural Computing and Applications 30 (1):163–81. doi:10.1007/s00521-016-2665-1.
- Goksal, F. P., I. Karaoglan, and F. Altiparmak. 2013. A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Computers & Industrial Engineering 65 (1):39–53. doi:10.1016/j.cie.2012.01.005.
- Kalayci, C. B., and C. Kaya. 2016. An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications 66:163–75. doi:10.1016/j.eswa.2016.09.017.
- Kang, F., J. Li, and Z. Ma. 2011. Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions. Information Sciences 181 (16):3508–31. doi:10.1016/j.ins.2011.04.024.
- Karaboga, D. 2005. An idea based on honey bee swarm for numerical optimization.
- Karaboga, D., and B. Akay. 2009. A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation 214 (1):108–32.
- Karaboga, D., and B. Akay Bilgisayar; Mühendisliği Bölümü Erciyes Üniversitesi. 2007. Artificial bee colony (ABC) algorithm on training artificial neural networks.
- Karaboga, D., and B. Basturk. 2007. A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization 39 (3):459–71. doi:10.1007/s10898-007-9149-x.
- Karaboga, D., and B. Gorkemli. 2012. A quick artificial bee colony -qABC- algorithm for optimization problems. INISTA 2012 : International Symposium on Innovations in Intelligent Systems and Applications 1–5. doi:10.1109/INISTA.2012.6247010.
- Karaboga, D., and B. Gorkemli. 2014. A quick artificial bee colony (qABC) algorithm and its performance on optimization problems. Applied Soft Computing 23:227–38. doi:10.1016/j.asoc.2014.06.035.
- Karaboga, D., B. Gorkemli, C. Ozturk, and N. Karaboga. 2014. A comprehensive survey: Artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review 42 (1):21–57. doi:10.1007/s10462-012-9328-0.
- Karaboga, D., and E. Kaya. 2016. An adaptive and hybrid artificial bee colony algorithm (aABC) for ANFIS training. Applied Soft Computing 49:423–36. doi:10.1016/j.asoc.2016.07.039.
- Kennedy, J., and R. Eberhart. 1995. Particle swarm optimization. Proceeding IEEE International Conference on Neural Networks 4:1942–48. vol.4.
- Kiran, M. S., E. Özceylan, M. Gündüz, and T. Paksoy. 2012. A novel hybrid approach based on particle swarm optimization and ant colony algorithm to forecast energy demand of Turkey. Energy Conversion and Management 53 (1):75–83. doi:10.1016/j.enconman.2011.08.004.
- Li, X., and G. Yang. 2016. Artificial bee colony algorithm with memory. Applied Soft Computing 41:362–72. doi:10.1016/j.asoc.2015.12.046.
- Qiu, J., Y. Shen, J. Xie, and J. Wang. 2013. Pbest-guided artificial bee colony algorithm for global numerical function optimization. International Journal of Applied Mathematics and Statistics 43 (13):117–25.
- Rao, R. V., and P. J. Pawar. 2009. Modelling and optimization of process parameters of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223 (11):1431–40. doi:10.1243/09544054JEM1559.
- Razali, N. M., and J. Geraghty. 2011. Genetic algorithm performance with different selection strategies in solving TSP. Proceedings of the World Congress on Engineering 2011 Vol II WCE 2011, July 6 - 8, 2011, London, UK.
- Rieck, J., and J. Zimmermann. 2013. Exact solutions to the symmetric and asymmetric vehicle routing problem with simultaneous delivery and pick-up. Business Research. 6 (1):77–92. doi:10.1007/BF03342743.
- Rizk-Allah, R. M., E. M. Zaki, and A. A. El-Sawy. 2013. Hybridizing ant colony optimization with firefly algorithm for unconstrained optimization problems. Applied Mathematics and Computation 224:473–83.
- Ropke, S., and D. Pisinger. 2006. A unified heuristic for a large class of vehicle routing problems with backhauls. European Journal of Operational Research 171 (3):750–75. doi:10.1016/j.ejor.2004.09.004.
- Rubio-Largo, A., D. L. Gonzalez-Alvarez, M. A. Vega-Rodriguez, J. A. Gomez-Pulido, and J. M. Sanchez-Perez. 2012. MO-ABC/DE-multiobjective artificial bee colony with differential evolution for unconstrained multiobjective optimization. CINTI 2012-13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings 157–62. doi:10.1109/CINTI.2012.6496752.
- Sayyah, M., H. Larki, and M. Yousefikhoshbakht. 2016. Solving the vehicle routing problem with simultaneous pickup and delivery by an effective ant colony optimization. Journal of Industrial Engineering and Management Studies 3 (1):15–38.
- Subramanian, A., L. M. A. Drummond, C. Bentes, L. S. Ochi, and R. Farias. 2010. A parallel heuristic for the vehicle routing problem with simultaneous pickup and delivery. Computers & Operations Research 37 (11):1899–911. doi:10.1016/j.cor.2009.10.011.
- Tuba, M., and N. Bacanin. 2014. Artificial bee colony algorithm hybridized with firefly algorithm for cardinality constrained mean-variance portfolio selection problem. Applied Mathematics & Information Sciences 8 (6):2831–44. doi:10.12785/amis/080619.
- Yang, X. S. 2013. Multiobjective firefly algorithm for continuous optimization. Engineering with Computers 29 (2):175–84. doi:10.1007/s00366-012-0254-1.
- Yang, X. S., and S. Deb. 2014. Cuckoo search: Recent advances and applications. Neural Computing & Applications 24 (1):169–74. doi:10.1007/s00521-013-1367-1.
- Yousefikhoshbakht, M., F. Didehvar, and F. Rahmati. 2014. A combination of modified tabu search and elite ant system to solve the vehicle routing problem with simultaneous pickup and delivery. Journal of Industrial and Production Engineering 31 (2):65–75.
- Zachariadis, E. E., C. D. Tarantilis, and C. T. Kiranoudis. 2009. A hybrid metaheuristic algorithm for the vehicle routing problem with simultaneous delivery and pick-up service. Expert Systems with Applications 36 (2 PART 1):1070–81. doi:10.1016/j.eswa.2007.11.005.
- Zhu, H., J. Feng, and H. Li. 2017. MN _ GLS for VRP with Simultaneous delivery and pickup. Journal of Computers, 28 (6):1–12. doi:10.3966/199115992017122806001.