Project
|
(Abd Elaziz et al., 2017Abd Elaziz, M., Oliva, D., & Xiong, S. (2017). An improved Opposition-Based Sine Cosine Algorithm for global optimization. Expert Systems with Applications, 90, 484-500. http://dx.doi.org/10.1016/j.eswa.2017.07.043. http://dx.doi.org/10.1016/j.eswa.2017.07...
; Adarsh et al., 2016Adarsh, B. R., Raghunathan, T., Jayabarathi, T., & Yang, X.-S. (2016). Economic dispatch using chaotic bat algorithm. Energy, 96, 666-675. http://dx.doi.org/10.1016/j.energy.2015.12.096. http://dx.doi.org/10.1016/j.energy.2015....
; Askarzadeh, 2016bAskarzadeh, A. (2016b). Capacitor placement in distribution systems for power loss reduction and voltage improvement: a new methodology. IET Generation, Transmission & Distribution, 10(14), 3631-3638. http://dx.doi.org/10.1049/iet-gtd.2016.0419. http://dx.doi.org/10.1049/iet-gtd.2016.0...
; Aydoğdu et al., 2016Aydoğdu, İ., Akın, A., & Saka, M. P. (2016). Design optimization of real world steel space frames using artificial bee colony algorithm with Levy flight distribution. Advances in Engineering Software, 92, 1-14. http://dx.doi.org/10.1016/j.advengsoft.2015.10.013. http://dx.doi.org/10.1016/j.advengsoft.2...
; Çaliş & Bulkan, 2015Çaliş, B., & Bulkan, S. (2015). A research survey: review of AI solution strategies of job shop scheduling problem. Journal of Intelligent Manufacturing, 26(5), 961-973. http://dx.doi.org/10.1007/s10845-013-0837-8. http://dx.doi.org/10.1007/s10845-013-083...
; Chen et al., 2016Chen, Z., Wu, L., Lin, P., Wu, Y., & Cheng, S. (2016). Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy. Applied Energy, 182, 47-57. http://dx.doi.org/10.1016/j.apenergy.2016.08.083. http://dx.doi.org/10.1016/j.apenergy.201...
; Chou & Pham, 2015Chou, J.-S., & Pham, A.-D. (2015). Smart artificial firefly colony algorithm-based support vector regression for enhanced forecasting in civil engineering. Computer-Aided Civil and Infrastructure Engineering, 30(9), 715-732. http://dx.doi.org/10.1111/mice.12121. http://dx.doi.org/10.1111/mice.12121...
; Ehsan & Yang, 2018Ehsan, A., & Yang, Q. (2018). Optimal integration and planning of renewable distributed generation in the power distribution networks: a review of analytical techniques. Applied Energy, 210, 44-59. http://dx.doi.org/10.1016/j.apenergy.2017.10.106. http://dx.doi.org/10.1016/j.apenergy.201...
; Fallah et al., 2018Fallah, S., Deo, R., Shojafar, M., Conti, M., & Shamshirband, S. (2018). Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions. Energies, 11(3), 596. http://dx.doi.org/10.3390/en11030596. http://dx.doi.org/10.3390/en11030596...
; García-Torres et al., 2016García-Torres, M., Gómez-Vela, F., Melián-Batista, B., & Moreno-Vega, J. M. (2016). High-dimensional feature selection via feature grouping: a variable neighborhood search approach. Information Sciences, 326, 102-118. http://dx.doi.org/10.1016/j.ins.2015.07.041. http://dx.doi.org/10.1016/j.ins.2015.07....
; Heidari et al., 2019Heidari, A. A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., & Chen, H. (2019). Harris hawks optimization: algorithm and applications. Future Generation Computer Systems, 97, 849-872. http://dx.doi.org/10.1016/j.future.2019.02.028. http://dx.doi.org/10.1016/j.future.2019....
; Karagöz & Yıldız, 2017Karagöz, S., & Yıldız, A. R. (2017). A comparison of recent metaheuristic algorithms for crashworthiness optimisation of vehicle thin-walled tubes considering sheet metal forming effects. International Journal of Vehicle Design, 73(1-3), 179. http://dx.doi.org/10.1504/IJVD.2017.082593. http://dx.doi.org/10.1504/IJVD.2017.0825...
; Labbi et al., 2016Labbi, Y., Attous, D. B., Gabbar, H. A., Mahdad, B., & Zidan, A. (2016). A new rooted tree optimization algorithm for economic dispatch with valve-point effect. International Journal of Electrical Power & Energy Systems, 79, 298-311. http://dx.doi.org/10.1016/j.ijepes.2016.01.028. http://dx.doi.org/10.1016/j.ijepes.2016....
; Maleki et al., 2016Maleki, A., Pourfayaz, F., & Ahmadi, M. H. (2016). Design of a cost-effective wind/photovoltaic/hydrogen energy system for supplying a desalination unit by a heuristic approach. Solar Energy, 139, 666-675. http://dx.doi.org/10.1016/j.solener.2016.09.028. http://dx.doi.org/10.1016/j.solener.2016...
; Mukhopadhyay et al., 2015Mukhopadhyay, A., Maulik, U., & Bandyopadhyay, S. (2015). A Survey of Multiobjective Evolutionary Clustering. ACM Computing Surveys, 47(4), 1-46. http://dx.doi.org/10.1145/2742642. http://dx.doi.org/10.1145/2742642...
; Nabil, 2016Nabil, E. (2016). A Modified Flower Pollination Algorithm for Global Optimization. Expert Systems with Applications, 57, 192-203. http://dx.doi.org/10.1016/j.eswa.2016.03.047. http://dx.doi.org/10.1016/j.eswa.2016.03...
; Osaba et al., 2016Osaba, E., Yang, X. S., Diaz, F., Lopez-Garcia, P., & Carballedo, R. (2016). An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems. Engineering Applications of Artificial Intelligence, 48, 59-71. http://dx.doi.org/10.1016/j.engappai.2015.10.006. http://dx.doi.org/10.1016/j.engappai.201...
; Rajpurohit et al., 2017Rajpurohit, J., Sharma, T. K., Abraham, A., & Vaishali. (2017). Glossary of metaheuristic algorithms. International Journal of Computer Information Systems and Industrial Management Applications, 9, 181-205.; Ramadan et al., 2017Ramadan, H. S., Bendary, A. F., & Nagy, S. (2017). Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators. International Journal of Electrical Power & Energy Systems, 84, 143-152. http://dx.doi.org/10.1016/j.ijepes.2016.04.041. http://dx.doi.org/10.1016/j.ijepes.2016....
; Sadollah et al., 2015Sadollah, A., Eskandar, H., Bahreininejad, A., & Kim, J. H. (2015). Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures. Computers & Structures, 149, 1-16. http://dx.doi.org/10.1016/j.compstruc.2014.12.003. http://dx.doi.org/10.1016/j.compstruc.20...
; Salido et al., 2016Salido, M. A., Escamilla, J., Giret, A., & Barber, F. (2016). A genetic algorithm for energy-efficiency in job-shop scheduling. International Journal of Advanced Manufacturing Technology, 85(5-8), 1303-1314. http://dx.doi.org/10.1007/s00170-015-7987-0. http://dx.doi.org/10.1007/s00170-015-798...
) |
Test
|
(Dell׳Amico et al., 2016Dell׳Amico, M., Iori, M., Novellani, S., & Stützle, T. (2016). A destroy and repair algorithm for the Bike sharing Rebalancing Problem. Computers & Operations Research, 71, 149-162. http://dx.doi.org/10.1016/j.cor.2016.01.011. http://dx.doi.org/10.1016/j.cor.2016.01....
; Faris et al., 2018Faris, H., Hassonah, M. A., Al-Zoubi, A. M., Mirjalili, S., & Aljarah, I. (2018). A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture. Neural Computing & Applications, 30(8), 2355-2369. http://dx.doi.org/10.1007/s00521-016-2818-2. http://dx.doi.org/10.1007/s00521-016-281...
; Kalra & Singh, 2015Kalra, M., & Singh, S. (2015). A review of metaheuristic scheduling techniques in cloud computing. Egyptian Informatics Journal, 16(3), 275-295. http://dx.doi.org/10.1016/j.eij.2015.07.001. http://dx.doi.org/10.1016/j.eij.2015.07....
; Mafarja et al., 2019Mafarja, M., Aljarah, I., Faris, H., Hammouri, A. I., Al-Zoubi, A. M., & Mirjalili, S. (2019). Binary grasshopper optimisation algorithm approaches for feature selection problems. Expert Systems with Applications, 117, 267-286. http://dx.doi.org/10.1016/j.eswa.2018.09.015. http://dx.doi.org/10.1016/j.eswa.2018.09...
; Medani et al., 2018Medani, K., Sayah, S., & Bekrar, A. (2018). Whale optimization algorithm based optimal reactive power dispatch: a case study of the Algerian power system. Electric Power Systems Research, 163, 696-705. http://dx.doi.org/10.1016/j.epsr.2017.09.001. http://dx.doi.org/10.1016/j.epsr.2017.09...
; Mellal & Williams, 2015Mellal, M. A., & Williams, E. J. (2015). Cuckoo optimization algorithm with penalty function for combined heat and power economic dispatch problem. Energy, 93, 1711-1718. http://dx.doi.org/10.1016/j.energy.2015.10.006. http://dx.doi.org/10.1016/j.energy.2015....
; Rafieerad et al., 2017Rafieerad, A. R., Bushroa, A. R., Nasiri-Tabrizi, B., Kaboli, S. H. A., Khanahmadi, S., Amiri, A., Vadivelu, J., Yusof, F., Basirun, W. J., & Wasa, K. (2017). Toward improved mechanical, tribological, corrosion and in-vitro bioactivity properties of mixed oxide nanotubes on Ti–6Al–7Nb implant using multi-objective PSO. Journal of the Mechanical Behavior of Biomedical Materials, 69, 1-18. http://dx.doi.org/10.1016/j.jmbbm.2016.11.019. PMid:28027481. http://dx.doi.org/10.1016/j.jmbbm.2016.1...
; Senthilnath et al., 2016Senthilnath, J., Kulkarni, S., Benediktsson, J. A., & Yang, X. S. (2016). A novel approach for multispectral satellite image classification based on the bat algorithm. IEEE Geoscience and Remote Sensing Letters, 13(4), 599-603. http://dx.doi.org/10.1109/LGRS.2016.2530724. http://dx.doi.org/10.1109/LGRS.2016.2530...
; Yu & Li, 2015Yu, J. J. Q., & Li, V. O. K. (2015). A social spider algorithm for global optimization. Applied Soft Computing, 30, 614-627. http://dx.doi.org/10.1016/j.asoc.2015.02.014. http://dx.doi.org/10.1016/j.asoc.2015.02...
) |
Implementation
|
(Ahmad et al., 2016Ahmad, M. W., Mourshed, M., Yuce, B., & Rezgui, Y. (2016). Computational intelligence techniques for HVAC systems: a review. Building Simulation, 9(4), 359-398. http://dx.doi.org/10.1007/s12273-016-0285-4. http://dx.doi.org/10.1007/s12273-016-028...
; Bandyopadhyay & Mukherjee, 2015Bandyopadhyay, S., & Mukherjee, A. (2015). An algorithm for many-objective optimization with reduced objective computations: a study in differential evolution. IEEE Transactions on Evolutionary Computation, 19(3), 400-413. http://dx.doi.org/10.1109/TEVC.2014.2332878. http://dx.doi.org/10.1109/TEVC.2014.2332...
; Dhiman & Kumar, 2017Dhiman, G., & Kumar, V. (2017). Spotted hyena optimizer: A novel bio-inspired based metaheuristic technique for engineering applications. Advances in Engineering Software, 114, 48-70. http://dx.doi.org/10.1016/j.advengsoft.2017.05.014. http://dx.doi.org/10.1016/j.advengsoft.2...
; Mitić et al., 2015Mitić, M., Vuković, N., Petrović, M., & Miljković, Z. (2015). Chaotic fruit fly optimization algorithm. Knowledge-Based Systems, 89(August), 446-458. http://dx.doi.org/10.1016/j.knosys.2015.08.010. http://dx.doi.org/10.1016/j.knosys.2015....
) |
Evaluation
|
(Abdullahi et al., 2016Abdullahi, M., Ngadi, M. A., & Abdulhamid, S. M. (2016). Symbiotic Organism Search optimization based task scheduling in cloud computing environment. Future Generation Computer Systems, 56, 640-650. http://dx.doi.org/10.1016/j.future.2015.08.006. http://dx.doi.org/10.1016/j.future.2015....
; Abualigah et al., 2018Abualigah, L. M., Khader, A. T., & Hanandeh, E. S. (2018). A new feature selection method to improve the document clustering using particle swarm optimization algorithm. Journal of Computational Science, 25, 456-466. http://dx.doi.org/10.1016/j.jocs.2017.07.018. http://dx.doi.org/10.1016/j.jocs.2017.07...
; Al-Dabbagh et al., 2018Al-Dabbagh, R. D., Neri, F., Idris, N., & Baba, M. S. (2018). Algorithmic design issues in adaptive differential evolution schemes: review and taxonomy. Swarm and Evolutionary Computation, 43, 284-311. http://dx.doi.org/10.1016/j.swevo.2018.03.008. http://dx.doi.org/10.1016/j.swevo.2018.0...
; Ari et al., 2016Ari, A. A. A., Yenke, B. O., Labraoui, N., Damakoa, I., & Gueroui, A. (2016). A power efficient cluster-based routing algorithm for wireless sensor networks: honeybees swarm intelligence based approach. Journal of Network and Computer Applications, 69, 77-97. http://dx.doi.org/10.1016/j.jnca.2016.04.020. http://dx.doi.org/10.1016/j.jnca.2016.04...
; Askarzadeh, 2016aAskarzadeh, A. (2016a). A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Computers & Structures, 169, 1-12. http://dx.doi.org/10.1016/j.compstruc.2016.03.001. http://dx.doi.org/10.1016/j.compstruc.20...
; Bagheri Tolabi et al., 2015Bagheri Tolabi, H., Ali, M. H., & Rizwan, M. (2015). Simultaneous reconfiguration, optimal placement of DSTATCOM, and photovoltaic array in a distribution system based on fuzzy-aco approach. IEEE Transactions on Sustainable Energy, 6(1), 210-218. http://dx.doi.org/10.1109/TSTE.2014.2364230. http://dx.doi.org/10.1109/TSTE.2014.2364...
; Caraveo et al., 2016Caraveo, C., Valdez, F., & Castillo, O. (2016). Optimization of fuzzy controller design using a new bee colony algorithm with fuzzy dynamic parameter adaptation. Applied Soft Computing, 43, 131-142. http://dx.doi.org/10.1016/j.asoc.2016.02.033. http://dx.doi.org/10.1016/j.asoc.2016.02...
; Chau, 2017Chau, K. (2017). Use of meta-heuristic techniques in rainfall-runoff modelling. Water, 9(3), 186. http://dx.doi.org/10.3390/w9030186. http://dx.doi.org/10.3390/w9030186...
; Dhiman & Kumar, 2018Dhiman, G., & Kumar, V. (2018). Emperor penguin optimizer: a bio-inspired algorithm for engineering problems. Knowledge-Based Systems, 159, 20-50. http://dx.doi.org/10.1016/j.knosys.2018.06.001. http://dx.doi.org/10.1016/j.knosys.2018....
; Hasançebi & Azad, 2015Hasançebi, O., & Azad, S. K. (2015). Adaptive dimensional search: a new metaheuristic algorithm for discrete truss sizing optimization. Computers & Structures, 154, 1-16. http://dx.doi.org/10.1016/j.compstruc.2015.03.014. http://dx.doi.org/10.1016/j.compstruc.20...
; Heidari et al., 2017Heidari, A. A., Ali Abbaspour, R., & Rezaee Jordehi, A. (2017). An efficient chaotic water cycle algorithm for optimization tasks. Neural Computing & Applications, 28(1), 57-85. http://dx.doi.org/10.1007/s00521-015-2037-2. http://dx.doi.org/10.1007/s00521-015-203...
; Saka et al., 2016Saka, M. P., Hasançebi, O., & Geem, Z. W. (2016). Metaheuristics in structural optimization and discussions on harmony search algorithm. Swarm and Evolutionary Computation, 28, 88-97. http://dx.doi.org/10.1016/j.swevo.2016.01.005. http://dx.doi.org/10.1016/j.swevo.2016.0...
; Saxena & Kothari, 2016Saxena, P., & Kothari, A. (2016). Ant Lion Optimization algorithm to control side lobe level and null depths in linear antenna arrays. AEÜ. International Journal of Electronics and Communications, 70(9), 1339-1349. http://dx.doi.org/10.1016/j.aeue.2016.07.008. http://dx.doi.org/10.1016/j.aeue.2016.07...
; Secui, 2016Secui, D. C. (2016). A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects. Energy, 113, 366-384. http://dx.doi.org/10.1016/j.energy.2016.07.056. http://dx.doi.org/10.1016/j.energy.2016....
; Silva et al., 2015Silva, T. M., Fo., Pimentel, B. A., Souza, R. M. C. R., & Oliveira, A. L. I. (2015). Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization. Expert Systems with Applications, 42(17-18), 6315-6328. http://dx.doi.org/10.1016/j.eswa.2015.04.032. http://dx.doi.org/10.1016/j.eswa.2015.04...
; Tien Bui et al., 2016Tien Bui, D., Pradhan, B., Nampak, H., Bui, Q.-T., Tran, Q.-A., & Nguyen, Q.-P. (2016). Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS. Journal of Hydrology, 540, 317-330. http://dx.doi.org/10.1016/j.jhydrol.2016.06.027. http://dx.doi.org/10.1016/j.jhydrol.2016...
) |