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Cable actuated parallel robots, despite their obvious benefits such as enhanced workspace, light weight, and flexibility, are not popularly used in ankle rehabilitation treatments, due to their complex mechanism and cable actuation issues. In order to address these issues, it is recommended to carry out robot design optimization. However, design synthesis of the cable actuated parallel ankle robot calls for multi-objective optimization (MOO), since there are multiple and conflicting objectives to achieve. To acquire more choices between actuator forces, overall stiffness of robot (which is crucial for a cable based ankle robot) and other vital design objectives, it is required to explore the extreme ends of the Pareto Front (PF) more carefully. Existing multi-objective evolutionary algorithms (MOEAs) normally focus on the convergence and may not provide solutions at the extremities of PF. Capitalizing on this improvement opportunity, this paper presents a fuzzy based MOEA, namely, biased fuzzy sorting genetic algorithm (BFSGA) which encourages solutions in the extreme zones of the PF. It is shown in this paper that using proposed method, diversity in the populations is supported and in the process wider trade-off choices of objectives can be obtained. During ankle robot design optimization, crisp objectives are defined as fuzzy objectives and competing solutions are provided an overall activation score (OAS). Subsequently OAS is used to assign a fuzzy dominance ranking to the design solutions. It is found that the BFSGA approach performs well in exploring the extreme zones of the Pareto front, which are normally overlooked by other MOEA such as NSGA-II due to their inherent mechanism.<\/jats:p>","DOI":"10.3233\/jifs-16030","type":"journal-article","created":{"date-parts":[[2016,8,19]],"date-time":"2016-08-19T10:27:17Z","timestamp":1471602437000},"page":"1897-1908","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":13,"title":["Design optimization of a cable actuated parallel ankle rehabilitation robot: A fuzzy based multi-objective evolutionary approach"],"prefix":"10.1177","volume":"31","author":[{"given":"Prashant K.","family":"Jamwal","sequence":"first","affiliation":[{"name":"Nazarbayev University","place":["Kazakhstan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahid","family":"Hussain","sequence":"additional","affiliation":[{"name":"University of Wollongong","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2016,6,23]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2012.2226596"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3109\/17483107.2013.866986"},{"key":"e_1_3_2_4_2","first-page":"701","article-title":"State-of-the-art robotic gait rehabilitation orthoses: Design and control aspects","volume":"35","author":"Hussain S.","year":"2014","unstructured":"HussainS., State-of-the-art robotic gait rehabilitation orthoses: Design and control aspects, Neuro Rehabilitation35 (2014), 701\u2013709.","journal-title":"Neuro Rehabilitation"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2012.2219065"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.medengphy.2012.02.003"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCA.2012.2207111"},{"key":"e_1_3_2_8_2","first-page":"1124","article-title":"Trajectory generation for ankle rehabilitation: A biomechanical model based approach","author":"Tsoi Y.H.","year":"2010","unstructured":"TsoiY.H. and XieS.Q., Trajectory generation for ankle rehabilitation: A biomechanical model based approach, in IET Seminar Digest, 2010, pp. 1124\u20131129.","journal-title":"in IET Seminar Digest"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2004.02.010"},{"key":"e_1_3_2_10_2","first-page":"1","article-title":"Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm","author":"Jamwal P.K.","year":"2014","unstructured":"JamwalP.K., HussainS. and XieS.Q., Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm, Automation Science and Engineering, IEEE Transactions on, 2014, pp. 1\u201314.","journal-title":"Automation Science and Engineering, IEEE Transactions on"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2015.2478389"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574714001416"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574711001032"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2011.11.004"},{"key":"e_1_3_2_15_2","article-title":"Some investigations into the optimal dimensional synthesis of parallel robots","author":"Kelaiaia R.","year":"2015","unstructured":"KelaiaiaR., ZaatriA., CompanyO. and ChikhL., Some investigations into the optimal dimensional synthesis of parallel robots, International Journal of Advanced Manufacturing Technology (2015).","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"e_1_3_2_16_2","volume-title":"World Scientific","author":"Coello C.A.C.","year":"2004","unstructured":"CoelloC.A.C. and LamontG.B., Applications of multi-objective evolutionary algorithms, World Scientific (2004). 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