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Ai, T. J., & Kachitvichyanukul, V. (2009). A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Computers & Operations Research, 36(5), 1693-1702.

Bianchessi, N., & Righini, G. (2007). Heuristic algorithms for the vehicle routing problem with simultaneous pick-up and delivery. Computers & Operations Research, 34(2), 578-594.

Christofides, N. (1976). The vehicle routing problem. Revue française d'automatique d'informatique et de recherche opérationnelle. Recherche opérationnelle, 10(1), 55-70.

Das, P., Behera, H., Jena, P., & Panigrahi, B. (2016). Multi-robot path planning in a dynamic environment using improved gravitational search algorithm. Journal of Electrical Systems and Information Technology, 3(2), 295-313.

Dell’Amico, M., Righini, G., & Salani, M. (2006). A branch-and-price approach to the vehicle routing problem with simultaneous distribution and collection. Transportation science, 40(2), 235-247.

Dethloff, J. (2001). Vehicle routing and reverse logistics: the vehicle routing problem with simultaneous delivery and pick-up. OR-Spektrum, 23(1), 79-96.

EBRAHIMI, M. S., RASHEDI, E., & JAVIDI, M. M. (2015). New functions for mass calculation in gravitational search algorithm.

González, B., Melin, P., Valdez, F., & Prado-Arechiga, G. (2018). Ensemble neural network optimization using a gravitational search algorithm with interval type-1 and type-2 fuzzy parameter adaptation in pattern recognition applications. In Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications (pp. 17-27): Springer.

Gupta, A., & Saini, S. (2017). On solutions to vehicle routing problems using swarm optimization techniques: a review. In Advances in Computer and Computational Sciences (pp. 345-354): Springer.

Hatamlou, A. (2013). Black hole: A new heuristic optimization approach for data clustering. Information sciences, 222, 175-184.

Kato, A., Nakamoto, Y., Ishimori, T., & Togashi, K. (2016). Predictability of Posthepatectomy Liver Failure (PHLF) using 99mTc-GSA scintigraphy. Journal of Nuclear Medicine, 57(supplement 2), 644-644.

Kherabadi, H. A., Mood, S. E., & Javidi, M. M. (2017). Mutation: a new operator in gravitational search algorithm using fuzzy controller. Cybernetics and Information Technologies, 17(1), 72-86.

Mohanty, D. K. (2016). Gravitational search algorithm for economic optimization design of a shell and tube heat exchanger. Applied Thermal Engineering, 107, 184-193.

Montané, F. A. T., & Galvao, R. D. (2006). A tabu search algorithm for the vehicle routing problem with simultaneous pick-up and delivery service. Computers & Operations Research, 33(3), 595-619.

Noel, M. M. (2012). A new gradient based particle swarm optimization algorithm for accurate computation of global minimum. Applied Soft Computing, 12(1), 353-359.

Rafsanjani, M. K., & Dowlatshahi, M. B. (2012). Using gravitational search algorithm for finding near-optimal base station location in two-tiered WSNs. International Journal of Machine Learning and Computing, 2(4), 377.

Rashedi, E., Nezamabadi-Pour, H., & Saryazdi, S. (2009). GSA: a gravitational search algorithm. Information sciences, 179(13), 2232-2248.

Rashedi, E., Nezamabadi-Pour, H., & Saryazdi, S. (2010). BGSA: binary gravitational search algorithm. Natural Computing, 9(3), 727-745.

Sabri, N. M., Puteh, M., & Mahmood, M. R. (2013). A review of gravitational search algorithm. Int. J. Advance. Soft Comput. Appl, 5(3), 1-39.

Shams, M., Rashedi, E., & Hakimi, A. (2015). Clustered-gravitational search algorithm and its application in parameter optimization of a low noise amplifier. Applied Mathematics and Computation, 258, 436-453.

Soleimanpour-Moghadam, M., Nezamabadi-Pour, H., & Farsangi, M. M. (2014). A quantum inspired gravitational search algorithm for numerical function optimization. Information sciences, 267, 83-100.

Tang, K., Yáo, X., Suganthan, P. N., MacNish, C., Chen, Y.-P., Chen, C.-M., & Yang, Z. (2007). Benchmark functions for the CEC’2008 special session and competition on large scale global optimization. Nature Inspired Computation and Applications Laboratory, USTC, China, 24.

Toth, P., & Vigo, D. (2002). The vehicle routing problem: SIAM.

Yao, B., Yu, B., Hu, P., Gao, J., & Zhang, M. (2016). An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot. Annals of Operations Research, 242(2), 303-320.

Zhang, J., & Sanderson, A. C. (2009). JADE: adaptive differential evolution with optional external archive. IEEE Transactions on evolutionary computation, 13(5), 945-958.

Zhang, J. T., & Qiao, L. X. (2013). Optimization Mechanism Control Strategy of Vehicle Routing Problem Based on Improved PSO. Paper presented at the Advanced Materials Research.