Publications

Poursalehi, N., Zolfaghari, A., & Minuchehr, A. (2013). PWR loading pattern optimization using Harmony Search algorithm. Annals of Nuclear Energy, 53, 288-298.

Aghaie, M., Nazari, T., Zolfaghari, A., Minuchehr, A., & Shirani, A. (2013). Investigation of PWR core optimization using harmony search algorithms. Annals of Nuclear Energy, 57, 1-15.

De Corte, A., & Sörensen, K. (2013). Optimisation of gravity-fed water distribution network design: A critical review. European Journal of Operational Research, 228(1), 1-10.

Yoon, S., Jeong, C., & Lee, T. (2013). Application of harmony search to design storm estimation from probability distribution models. Journal of Applied Mathematics, 2013.

Ayvaz, M. T., & Elçi, A. (2013). A groundwater management tool for solving the pumping cost minimization problem for the Tahtali watershed (Izmir-Turkey) using hybrid HS-Solver optimization algorithm. Journal of Hydrology, 478, 63-76.

Cheraghalipour, A., Hajiaghaei-Keshteli, M., & Paydar, M. M. (2018). Tree Growth Algorithm (TGA): A novel approach for solving optimization problems. Engineering Applications of Artificial Intelligence, 72, 393-414.

Duc, L. A., Li, K., Nguyen, T. T., Yen, V. M., & Truong, T. K. (2018). A new effective operator for the hybrid algorithm for solving global optimisation problems. International Journal of Systems Science, 49(5), 1088-1102.

Zhuoran, Z., Changqiang, H., Hanqiao, H., Shangqin, T., & Kangsheng, D. (2018). An optimization method: hummingbirds optimization algorithm. Journal of Systems Engineering and Electronics, 29(2), 386-404.

Yassine, A. A., Kingsford, W., Xu, Y., Cassidy, J., Lilge, L., & Betz, V. (2018). Automatic interstitial photodynamic therapy planning via convex optimization. Biomedical optics express, 9(2), 898-920.

Mitikiri, P., Jana, G., Sural, S., & Chattaraj, P. K. (2018). A machine learning technique toward generating minimum energy structures of small boron clusters.

Sur, C., & Shukla, A. (2018). Discrete bacteria foraging optimization algorithm for graph based problems–a transition from continuous to discrete. Journal of Experimental & Theoretical Artificial Intelligence, 30(2), 345-365.

Abdel-Basset, M., Hessin, A. N., & Abdel-Fatah, L. (2018). A comprehensive study of cuckoo-inspired algorithms. Neural Computing and Applications, 29(2), 345-361.

Nabaei, A., Hamian, M., Parsaei, M. R., Safdari, R., Samad-Soltani, T., Zarrabi, H., & Ghassemi, A. (2018). Topologies and performance of intelligent algorithms: a comprehensive review. Artificial Intelligence Review, 49(1), 79-103.

Osaba, E., Carballedo, R., Diaz, F., Onieva, E., Masegosa, A. D., & Perallos, A. (2018). Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems. Neurocomputing, 271, 2-8.

García, J., Crawford, B., Soto, R., Castro, C., & Paredes, F. (2018). A k-means binarization framework applied to multidimensional knapsack problem. Applied Intelligence, 48(2), 357-380.

Fattahi, E., Bidar, M., & Kanan, H. R. (2018). Focus group: an optimization algorithm inspired by human behavior. International Journal of Computational Intelligence and Applications, 17(01), 1850002.

Borkar, P., & Sarode, M. V. (2018). Modality of teaching learning based optimization algorithm to reduce the consistency ratio of the pair-wise comparison matrix in analytical hierarchy processing. Evolving Systems, 9(2), 169-180.

Ghanem, W. A., & Jantan, A. (2018). Hybridizing artificial bee colony with monarch butterfly optimization for numerical optimization problems. Neural Computing and Applications, 30(1), 163-181.

Nayak, J., Naik, B., Behera, H. S., & Abraham, A. (2018). Elitist teaching–learning-based optimization (ETLBO) with higher-order Jordan Pi-sigma neural network: a comparative performance analysis. Neural Computing and Applications, 30(5), 1445-1468.

Liu, W., Luo, N., Pan, G., & Ouyang, A. (2018). Chaos particle swarm optimization algorithm for optimization problems. International Journal of Pattern Recognition and Artificial Intelligence, 32(11), 1859019.