{"_id":"54000","publication_identifier":{"issn":["0941-0643","1433-3058"]},"language":[{"iso":"eng"}],"doi":"10.1007/s00521-016-2676-y","year":"2018","author":[{"full_name":"Tavana, Madjid","last_name":"Tavana","first_name":"Madjid","id":"31858"},{"full_name":"Khalili-Damghani, Kaveh","last_name":"Khalili-Damghani","first_name":"Kaveh"},{"first_name":"Debora","full_name":"Di Caprio, Debora","last_name":"Di Caprio"},{"first_name":"Zeynab","full_name":"Oveisi, Zeynab","last_name":"Oveisi"}],"issue":"1","citation":{"ieee":"M. Tavana, K. Khalili-Damghani, D. Di Caprio, and Z. Oveisi, “An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems,” <i>Neural Computing and Applications</i>, vol. 30, no. 1, pp. 127–139, 2018, doi: <a href=\"https://doi.org/10.1007/s00521-016-2676-y\">10.1007/s00521-016-2676-y</a>.","apa":"Tavana, M., Khalili-Damghani, K., Di Caprio, D., &#38; Oveisi, Z. (2018). An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems. <i>Neural Computing and Applications</i>, <i>30</i>(1), 127–139. <a href=\"https://doi.org/10.1007/s00521-016-2676-y\">https://doi.org/10.1007/s00521-016-2676-y</a>","bibtex":"@article{Tavana_Khalili-Damghani_Di Caprio_Oveisi_2018, title={An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems}, volume={30}, DOI={<a href=\"https://doi.org/10.1007/s00521-016-2676-y\">10.1007/s00521-016-2676-y</a>}, number={1}, journal={Neural Computing and Applications}, publisher={Springer Science and Business Media LLC}, author={Tavana, Madjid and Khalili-Damghani, Kaveh and Di Caprio, Debora and Oveisi, Zeynab}, year={2018}, pages={127–139} }","mla":"Tavana, Madjid, et al. “An Evolutionary Computation Approach to Solving Repairable Multi-State Multi-Objective Redundancy Allocation Problems.” <i>Neural Computing and Applications</i>, vol. 30, no. 1, Springer Science and Business Media LLC, 2018, pp. 127–39, doi:<a href=\"https://doi.org/10.1007/s00521-016-2676-y\">10.1007/s00521-016-2676-y</a>.","ama":"Tavana M, Khalili-Damghani K, Di Caprio D, Oveisi Z. An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems. <i>Neural Computing and Applications</i>. 2018;30(1):127-139. doi:<a href=\"https://doi.org/10.1007/s00521-016-2676-y\">10.1007/s00521-016-2676-y</a>","chicago":"Tavana, Madjid, Kaveh Khalili-Damghani, Debora Di Caprio, and Zeynab Oveisi. “An Evolutionary Computation Approach to Solving Repairable Multi-State Multi-Objective Redundancy Allocation Problems.” <i>Neural Computing and Applications</i> 30, no. 1 (2018): 127–39. <a href=\"https://doi.org/10.1007/s00521-016-2676-y\">https://doi.org/10.1007/s00521-016-2676-y</a>.","short":"M. Tavana, K. Khalili-Damghani, D. Di Caprio, Z. Oveisi, Neural Computing and Applications 30 (2018) 127–139."},"intvolume":"        30","user_id":"51811","page":"127-139","status":"public","date_created":"2024-05-06T16:49:59Z","date_updated":"2024-05-06T16:58:52Z","publication":"Neural Computing and Applications","title":"An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems","department":[{"_id":"277"}],"publisher":"Springer Science and Business Media LLC","volume":30,"publication_status":"published","type":"journal_article"}