{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T20:00:56Z","timestamp":1760731256421,"version":"build-2065373602"},"reference-count":103,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T00:00:00Z","timestamp":1572998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A significant challenge in neuroscience is understanding how visual information is encoded in the retina. Such knowledge is extremely important for the purpose of designing bioinspired sensors and artificial retinal systems that will, in so far as may be possible, be capable of mimicking vertebrate retinal behaviour. In this study, we report the tuning of a reliable computational bioinspired retinal model with various algorithms to improve the mimicry of the model. Its main contribution is two-fold. First, given the multi-objective nature of the problem, an automatic multi-objective optimisation strategy is proposed through the use of four biological-based metrics, which are used to adjust the retinal model for accurate prediction of retinal ganglion cell responses. Second, a subset of population-based search heuristics\u2014genetic algorithms (SPEA2, NSGA-II and NSGA-III), particle swarm optimisation (PSO) and differential evolution (DE)\u2014are explored to identify the best algorithm for fine-tuning the retinal model, by comparing performance across a hypervolume metric. Nonparametric statistical tests are used to perform a rigorous comparison between all the metaheuristics. The best results were achieved with the PSO algorithm on the basis of the largest hypervolume that was achieved, well-distributed elements and high numbers on the Pareto front.<\/jats:p>","DOI":"10.3390\/s19224834","type":"journal-article","created":{"date-parts":[[2019,11,7]],"date-time":"2019-11-07T06:52:36Z","timestamp":1573109556000},"page":"4834","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Metaheuristic Optimisation Algorithms for Tuning a Bioinspired Retinal Model"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8751-0000","authenticated-orcid":false,"given":"Rub\u00e9n","family":"Crespo-Cano","sequence":"first","affiliation":[{"name":"Department of Computer Technology, University of Alicante, 03690 Alicante, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5830-6104","authenticated-orcid":false,"given":"Sergio","family":"Cuenca-Asensi","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, University of Alicante, 03690 Alicante, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0401-2733","authenticated-orcid":false,"given":"Eduardo","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Institute of Bioengineering, University Miguel Hern\u00e1ndez and CIBER BBN, 03202 Elche (Alicante), Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1500-857X","authenticated-orcid":false,"given":"Antonio","family":"Mart\u00ednez-\u00c1lvarez","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, University of Alicante, 03690 Alicante, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,6]]},"reference":[{"key":"ref_1","unstructured":"WHO (2014). Visual Impairment and Blindness, WHO."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1038\/eye.2017.65","article-title":"Electronic retinal implants and artificial vision: Journey and present","volume":"31","author":"Mills","year":"2017","journal-title":"Eye"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.brainres.2014.11.020","article-title":"Restoration of vision in blind individuals using bionic devices: A review with a focus on cortical visual prostheses","volume":"1595","author":"Lewis","year":"2015","journal-title":"Brain Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1111\/ans.13616","article-title":"Advances in implantable bionic devices for blindness: A review","volume":"86","author":"Lewis","year":"2016","journal-title":"ANZ J. Surg."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s42234-018-0013-8","article-title":"Development of visual Neuroprostheses: Trends and challenges","volume":"4","author":"Fernandez","year":"2018","journal-title":"Bioelectron. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1650021","DOI":"10.1142\/S0129065716500210","article-title":"Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm","volume":"26","year":"2016","journal-title":"Int. J. Neural Syst."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Crespo-Cano, R., Mart\u00ednez-\u00c1lvarez, A., Cuenca-Asensi, S., and Fern\u00e1ndez, E. (2017). Assessment and Comparison of Evolutionary Algorithms for Tuning a Bioinspired Retinal Model. Natural and Artificial Computation for Biomedicine and Neuroscience: International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, Springer International Publishing.","DOI":"10.1007\/978-3-319-59740-9_10"},{"key":"ref_8","first-page":"24","article-title":"Acute human brain responses to intracortical microelectrode arrays: Challenges and future prospects","volume":"7","author":"Greger","year":"2014","journal-title":"Front. Neuroeng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez, E., and Normann, R.A. (2017). CORTIVIS Approach for an Intracortical Visual Prostheses. Artificial Vision: A Clinical Guide, Springer International Publishing.","DOI":"10.1007\/978-3-319-41876-6_15"},{"key":"ref_10","first-page":"348","article-title":"The vertebrate eye and its adaptive radiation","volume":"17","author":"Walls","year":"1942","journal-title":"Anat. Rec."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1152\/jn.1953.16.1.37","article-title":"Discharge patterns and functional organization of mammalian retina","volume":"16","author":"Kuffler","year":"1953","journal-title":"J. Neurophysiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1136\/bjo.58.11.948-c","article-title":"The vertebrate retina: Principles of structure and function","volume":"58","author":"Rodieck","year":"1974","journal-title":"Br. J. Ophthalmol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1126\/science.2035024","article-title":"Synchronous bursts of action potentials in ganglion cells of the developing mammalian retina","volume":"252","author":"Meister","year":"1991","journal-title":"Science"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1001\/archopht.1994.01090130120028","article-title":"Bipolar surface electrical stimulation of the vertebrate retina","volume":"112","author":"Humayun","year":"1994","journal-title":"Arch. Ophthalmol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1073\/pnas.93.2.589","article-title":"Cell fate determination in the vertebrate retina","volume":"93","author":"Cepko","year":"1996","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1038\/nn0901-877","article-title":"The fundamental plan of the retina","volume":"4","author":"Masland","year":"2001","journal-title":"Nat. Neurosci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1146\/annurev.neuro.30.051606.094252","article-title":"Information processing in the primate retina: Circuitry and coding","volume":"30","author":"Field","year":"2007","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_18","unstructured":"Thorpe, S.A., and Glickstein, M. (1972). The Structure of the Retina, 1892, Thomas. Transl."},{"key":"ref_19","unstructured":"Kolb, H., Fernandez, E., and Nelson, R. (1995). Webvision: The Organization of the Retina and Visual System, University of Utah Health Sciences Center."},{"key":"ref_20","unstructured":"Simoncelli, E., Pillow, J., Paninski, L., and Schwartz, O. (2004). Characterization of neural responses with stochastic stimuli. The Cognitive Neurosciences, III, MIT Press."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/S0079-6123(06)65031-0","article-title":"Statistical models for neural encoding, decoding, and optimal stimulus design","volume":"165","author":"Paninski","year":"2007","journal-title":"Prog. Brain Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1038\/nature07140","article-title":"Spatio-temporal correlations and visual signalling in a complete neuronal population","volume":"454","author":"Pillow","year":"2008","journal-title":"Nature"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"15012","DOI":"10.1073\/pnas.1207035109","article-title":"Retinal prosthetic strategy with the capacity to restore normal vision","volume":"109","author":"Nirenberg","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Bomash, I., Roudi, Y., and Nirenberg, S. (2013). A virtual retina for studying population coding. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0053363"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1109\/TNSRE.2017.2763130","article-title":"An Embedded Real-time Processing Platform for Optogenetic Neuroprosthetic Applications","volume":"26","author":"Yan","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1007\/s10827-008-0108-4","article-title":"Virtual retina: A biological retina model and simulator, with contrast gain control","volume":"26","author":"Wohrer","year":"2009","journal-title":"J. Comput. Neurosci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"49","DOI":"10.3389\/fninf.2017.00049","article-title":"PRANAS: A new platform for retinal analysis and simulation","volume":"11","author":"Cessac","year":"2017","journal-title":"Front. Neuroinformatics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"9","DOI":"10.3389\/fninf.2018.00009","article-title":"Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing","volume":"12","author":"Huth","year":"2018","journal-title":"Front. Neuroinformatics"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.neucom.2012.07.035","article-title":"RetinaStudio: A bioinspired framework to encode visual information","volume":"114","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1650030","DOI":"10.1142\/S0129065716500301","article-title":"A computational framework for realistic retina modelling","volume":"26","author":"Morillas","year":"2016","journal-title":"Int. J. Neural Syst."},{"key":"ref_31","unstructured":"Lee, D.D., Sugiyama, M., Luxburg, U.V., Guyon, I., and Garnett, R. (2016). Deep Learning Models of the Retinal Response to Natural Scenes. Advances in Neural Information Processing Systems 29, Curran Associates, Inc."},{"key":"ref_32","unstructured":"Maheswaranathan, N., McIntosh, L.T., Kastner, D.B., Melander, J., Brezovec, L., Nayebi, A., Wang, J., Ganguli, S., and Baccus, S.A. (2018). Deep learning models reveal internal structure and diverse computations in the retina under natural scenes. bioRxiv, 340943."},{"key":"ref_33","unstructured":"Batty, E., Merel, J., Brackbill, N., Heitman, A., Sher, A., Litke, A., Chichilnisky, E., and Paninski, L. (2016, January 2\u20134). Multilayer recurrent network models of primate retinal ganglion cell responses. Proceedings of the International Conference on Learning Representations, Vancouver, BC, Canada."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1136\/bjophthalmol-2012-301525","article-title":"The Argus II epiretinal prosthesis system allows letter and word reading and long-term function in patients with profound vision loss","volume":"97","author":"Coley","year":"2013","journal-title":"Br. J. Ophthalmol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1586\/17434440.2014.862494","article-title":"The functional performance of the Argus II retinal prosthesis","volume":"11","author":"Stronks","year":"2014","journal-title":"Expert Rev. Med. Devices"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"20130077","DOI":"10.1098\/rspb.2013.0077","article-title":"Artificial vision with wirelessly powered subretinal electronic implant alpha-IMS","volume":"280","author":"Stingl","year":"2013","journal-title":"Proc. R. Soc. B Biol. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.visres.2015.03.001","article-title":"Subretinal visual implant alpha IMS\u2013clinical trial interim report","volume":"111","author":"Stingl","year":"2015","journal-title":"Vis. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1097\/WNO.0b013e31821eb79e","article-title":"Update on retinal prosthetic research: The Boston Retinal Implant Project","volume":"31","year":"2011","journal-title":"J. Neuro-Ophthalmol."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Hornig, R., Dapper, M., Le Joliff, E., Hill, R., Ishaque, K., Posch, C., Benosman, R., LeMer, Y., Sahel, J.A., and Picaud, S. (2017). Pixium Vision: First Clinical Results and Innovative Developments. Artificial Vision, Springer.","DOI":"10.1007\/978-3-319-41876-6_8"},{"key":"ref_40","first-page":"3009","article-title":"The EPI RET3 Wireless Intraocular Retina Implant System: Biocompatibility of the EPI RET3 Device","volume":"49","author":"Sellhaus","year":"2008","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Lowery, A.J. (2013, January 15\u201318). Introducing the monash vision group\u2019s cortical prosthesis. Proceedings of the 2013 20th IEEE International Conference on Image Processing (ICIP), Melbourne, VIC, Australia.","DOI":"10.1109\/ICIP.2013.6738316"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"8","DOI":"10.3389\/fneng.2010.00008","article-title":"Biocompatibility of intracortical microelectrodes: Current status and future prospects","volume":"3","author":"Marin","year":"2010","journal-title":"Front. Neuroeng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/0042-6989(65)90033-7","article-title":"Quantitative analysis of cat retinal ganglion cell response to visual stimuli","volume":"5","author":"Rodieck","year":"1965","journal-title":"Vis. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1113\/jphysiol.1966.sp008107","article-title":"The contrast sensitivity of retinal ganglion cells of the cat","volume":"187","author":"Robson","year":"1966","journal-title":"J. Physiol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1098\/rspb.1980.0020","article-title":"Theory of edge detection","volume":"207","author":"Marr","year":"1980","journal-title":"Proc. R. Soc. Lond. B Biol. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/S0361-9230(99)00161-6","article-title":"Lapicque\u2019s introduction of the integrate-and-fire model neuron (1907)","volume":"50","author":"Abbott","year":"1999","journal-title":"Brain Res. Bull."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00422-006-0068-6","article-title":"A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input","volume":"95","author":"Burkitt","year":"2006","journal-title":"Biol. Cybern."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s00422-007-0190-0","article-title":"Lapicque\u2019s 1907 paper: From frogs to integrate-and-fire","volume":"97","author":"Brunel","year":"2007","journal-title":"Biol. Cybern."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1016\/j.cviu.2010.01.011","article-title":"Using Human Visual System modelling for bioinspired low level image processing","volume":"114","author":"Benoit","year":"2010","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.ins.2013.02.041","article-title":"A survey on optimization metaheuristics","volume":"237","author":"Lepagnot","year":"2013","journal-title":"Inf. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Darwin, C. (2004). On the Origin of Species, 1859, Routledge.","DOI":"10.4324\/9780203509104"},{"key":"ref_52","unstructured":"Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc.. [1st ed.]."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Holland, J.H. (1992). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, MIT Press.","DOI":"10.7551\/mitpress\/1090.001.0001"},{"key":"ref_54","unstructured":"Koza, J.R., and Koza, J.R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press."},{"key":"ref_55","unstructured":"Rechenberg, I. (1965). Cybernetic Solution Path of an Experimental Problem, Royal Aircraft Establishment Library Translation No. 1122."},{"key":"ref_56","unstructured":"Reynolds, R.G. (1994, January 24\u201326). An introduction to cultural algorithms. Proceedings of the Third Annual Conference on Evolutionary Programming, River Edge, NJ, USA."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Kennedy, J. (2011). Particle swarm optimization. Encyclopedia of Machine Learning, Springer.","DOI":"10.1007\/978-0-387-30164-8_630"},{"key":"ref_58","unstructured":"Walker, A., Hallam, J., and Willshaw, D. (April, January 28). Bee-havior in a mobile robot: The construction of a self-organized cognitive map and its use in robot navigation within a complex, natural environment. Proceedings of the IEEE International Conference on Neural Networks, San Francisco, CA, USA."},{"key":"ref_59","unstructured":"Dorigo, M. (1992). Optimization, Learning and Natural Algorithms. [Ph.D. Thesis, Politecnico di Milano]."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/MCS.2002.1004010","article-title":"Biomimicry of bacterial foraging for distributed optimization and control","volume":"22","author":"Passino","year":"2002","journal-title":"IEEE Control Syst. Mag."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Ren, M., Song, Y., and Chu, W. (2019). An Improved Locally Weighted PLS Based on Particle Swarm Optimization for Industrial Soft Sensor Modeling. Sensors, 19.","DOI":"10.3390\/s19194099"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Liu, N., Pan, J.S., Wang, J., and Nguyen, T.T. (2019). An Adaptation Multi-Group Quasi-Affine Transformation Evolutionary Algorithm for Global Optimization and Its Application in Node Localization in Wireless Sensor Networks. Sensors, 19.","DOI":"10.3390\/s19194112"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Strumberger, I., Minovic, M., Tuba, M., and Bacanin, N. (2019). Performance of Elephant Herding Optimization and Tree Growth Algorithm Adapted for Node Localization in Wireless Sensor Networks. Sensors, 19.","DOI":"10.3390\/s19112515"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Paul, A., and Sato, T. (2017). Localization in wireless sensor networks: A survey on algorithms, measurement techniques, applications and challenges. J. Sens. Actuator Netw., 6.","DOI":"10.3390\/jsan6040024"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Strumberger, I., Tuba, E., Bacanin, N., Beko, M., and Tuba, M. (2018, January 25\u201329). Wireless Sensor Network Localization Problem by Hybridized Moth Search Algorithm. Proceedings of the 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), Limassol, Cyprus.","DOI":"10.1109\/IWCMC.2018.8450491"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.asoc.2018.03.039","article-title":"Localization in wireless sensor networks: A dimension based pruning approach in 3D environments","volume":"68","author":"Raguraman","year":"2018","journal-title":"Appl. Soft Comput."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Wu, T.Y., Lin, J.C.W., Zhang, Y., and Chen, C.H. (2019). A Grid-Based Swarm Intelligence Algorithm for Privacy-Preserving Data Mining. Appl. Sci., 9.","DOI":"10.3390\/app9040774"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Wang, C., Shi, Z., and Wu, F. (2017). An improved particle swarm optimization-based feed-forward neural network combined with RFID sensors to indoor localization. Information, 8.","DOI":"10.3390\/info8010009"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Bacanin, N., Tuba, M., and Strumberger, I. (2015, January 25\u201327). RFID network planning by ABC algorithm hybridized with heuristic for initial number and locations of readers. Proceedings of the 2015 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim), Cambridge, UK.","DOI":"10.1109\/UKSim.2015.83"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_71","unstructured":"Zitzler, E., and Thiele, L. (2019, November 06). An Evolutionary Algorithm for Multiobjective Optimization: The Strength Pareto Approach. Available online: https:\/\/www.research-collection.ethz.ch\/bitstream\/handle\/20.500.11850\/145900\/eth-24834-01.pdf."},{"key":"ref_72","unstructured":"Zitzler, E., Laumanns, M., and Thiele, L. (2019, November 06). SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Available online: https:\/\/www.research-collection.ethz.ch\/bitstream\/handle\/20.500.11850\/145755\/eth-24689-01.pdf."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Corne, D.W., Knowles, J.D., and Oates, M.J. (2000). The Pareto envelope-based selection algorithm for multiobjective optimization. International Conference on Parallel Problem Solving from Nature, Springer.","DOI":"10.1007\/3-540-45356-3_82"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","article-title":"An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: Solving problems with box constraints","volume":"18","author":"Deb","year":"2014","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1007\/s10044-005-0015-5","article-title":"Dynamic clustering using particle swarm optimization with application in image segmentation","volume":"8","author":"Omran","year":"2006","journal-title":"Pattern Anal. Appl."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1109\/TAP.2004.823969","article-title":"Particle swarm optimization in electromagnetics","volume":"52","author":"Robinson","year":"2004","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Pandey, S., Wu, L., Guru, S.M., and Buyya, R. (2010, January 20\u201323). A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments. Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications (AINA), Perth, WA, Australia.","DOI":"10.1109\/AINA.2010.31"},{"key":"ref_78","unstructured":"Shi, Y., and Eberhart, R. (1998, January 4\u20139). A modified particle swarm optimizer. Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Anchorage, AK, USA."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1109\/TEVC.2004.826071","article-title":"Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients","volume":"8","author":"Ratnaweera","year":"2004","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/TEVC.2005.857610","article-title":"Comprehensive learning particle swarm optimizer for global optimization of multimodal functions","volume":"10","author":"Liang","year":"2006","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_81","first-page":"287","article-title":"Multi-objective particle swarm optimizers: A survey of the state-of-the-art","volume":"2","author":"Coello","year":"2006","journal-title":"Int. J. Comput. Intell. Res."},{"key":"ref_82","unstructured":"Storn, R., and Price, K. (1995). Differential Evolution\u2014A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces, ICSI Berkeley."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Robi\u010d, T., and Filipi\u010d, B. (2005). DEMO: Differential evolution for multiobjective optimization. International Conference on Evolutionary Multi-Criterion Optimization, Springer.","DOI":"10.1007\/978-3-540-31880-4_36"},{"key":"ref_84","first-page":"222","article-title":"Population coding in spike trains of simultaneously recorded retinal ganglion cells11Published on the World Wide Web on 7 November 2000","volume":"887","author":"Ferrandez","year":"2000","journal-title":"Brain Res."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1007\/978-3-319-18914-7_23","article-title":"Towards the Reconstruction of Moving Images by Populations of Retinal Ganglion Cells","volume":"Volume 9107","author":"Humphreys","year":"2015","journal-title":"Artificial Computation in Biology and Medicine"},{"key":"ref_86","unstructured":"Kullback, S. (1997). Information Theory and Statistics, Courier Corporation."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Zitzler, E., and Thiele, L. (1998). Multiobjective optimization using evolutionary algorithms\u2014A comparative case study. International Conference on Parallel Problem Solving from Nature, Springer.","DOI":"10.1007\/BFb0056872"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/4235.797969","article-title":"Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach","volume":"3","author":"Zitzler","year":"1999","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/TEVC.2003.810758","article-title":"Performance assessment of multiobjective optimizers: An analysis and review","volume":"7","author":"Zitzler","year":"2003","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Fleischer, M. (2003). The measure of Pareto optima applications to multi-objective metaheuristics. Evolutionary Multi-Criterion Optimization, Springer.","DOI":"10.21236\/ADA441037"},{"key":"ref_91","unstructured":"Van Veldhuizen, D.A., and Lamont, G.B. (2019, November 06). Multiobjective Evolutionary Algorithm Research: A History and Analysis. Available online: citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.35.8924&rep=rep1&type=pdf."},{"key":"ref_92","unstructured":"Tukey, J.W. (1977). Exploratory Data Analysis, Addison-Wesley Publishing Company."},{"key":"ref_93","unstructured":"Chambers, J.M. (1983). Graphical Methods for Data Analysis, Duxbury Press."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1080\/01621459.1952.10483441","article-title":"Use of Ranks in One-Criterion Variance Analysis","volume":"47","author":"Kruskal","year":"1952","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","article-title":"The use of ranks to avoid the assumption of normality implicit in the analysis of variance","volume":"32","author":"Friedman","year":"1937","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1214\/aoms\/1177731944","article-title":"A comparison of alternative tests of significance for the problem of m rankings","volume":"11","author":"Friedman","year":"1940","journal-title":"Ann. Math. Stat."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"80","DOI":"10.2307\/3001968","article-title":"Individual comparisons by ranking methods","volume":"1","author":"Wilcoxon","year":"1945","journal-title":"Biom. Bull."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1214\/aoms\/1177730491","article-title":"On a test of whether one of two random variables is stochastically larger than the other","volume":"18","author":"Mann","year":"1947","journal-title":"Ann. Math. Stat."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1080\/01621459.1961.10482090","article-title":"Multiple comparisons among means","volume":"56","author":"Dunn","year":"1961","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1093\/biomet\/75.4.800","article-title":"A sharper Bonferroni procedure for multiple tests of significance","volume":"75","author":"Hochberg","year":"1988","journal-title":"Biometrika"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1093\/biomet\/75.2.383","article-title":"A stagewise rejective multiple test procedure based on a modified Bonferroni test","volume":"75","author":"Hommel","year":"1988","journal-title":"Biometrika"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1162\/EVCO_a_00009","article-title":"HypE: An algorithm for fast hypervolume-based many-objective optimization","volume":"19","author":"Bader","year":"2011","journal-title":"Evol. Comput."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1080\/713663221","article-title":"A simple white noise analysis of neuronal light responses","volume":"12","author":"Chichilnisky","year":"2001","journal-title":"Netw. Comput. 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