{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T21:44:31Z","timestamp":1787694271404,"version":"build-2784847793"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Syst Assur Eng Manag"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s13198-024-02556-9","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T21:02:06Z","timestamp":1729544526000},"page":"5653-5675","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic motion based evolutionary algorithm for enhancement of the search capability for global search space"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3240-1573","authenticated-orcid":false,"given":"Nidhi","family":"Parashar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deependra","family":"Rastogi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prashant","family":"Johri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sunil Kumar","family":"Khatri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudeept Singh","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Methily","family":"Johri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"2556_CR1","doi-asserted-by":"crossref","unstructured":"Abdelkhalek M, Amor S.B, Affes S (2022), May. Blind ML JADE in Multipath Environments Using Differential Evolution. In ICC 2022-IEEE International Conference on Communications (pp. 1787-1792). IEEE","DOI":"10.1109\/ICC45855.2022.9838663"},{"issue":"1","key":"2556_CR2","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/S0965-9978(00)00070-3","volume":"32","author":"J Andre","year":"2001","unstructured":"Andre J, Siarry P, Dognon T (2001) An improvement of the standard genetic algorithm fighting premature convergence in continuous optimization. Adv Eng Softw 32(1):49\u201360","journal-title":"Adv Eng Softw"},{"key":"2556_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105739","volume":"119","author":"H Chen","year":"2023","unstructured":"Chen H, Li S, Li X, Zhao Y, Dong J (2023) A hybrid adaptive differential evolution based on Gaussian tail mutation. Eng Appl Artif Intell 119:105739","journal-title":"Eng Appl Artif Intell"},{"key":"2556_CR4","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.ins.2017.09.002","volume":"422","author":"L Cui","year":"2018","unstructured":"Cui L, Li G, Zhu Z, Lin Q, Wong KC, Chen J, Lu N, Lu J (2018) Adaptive multiple-elites-guided composite differential evolution algorithm with a shift mechanism. Inf Sci 422:122\u2013143","journal-title":"Inf Sci"},{"key":"2556_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120524","volume":"668","author":"Z Cui","year":"2024","unstructured":"Cui Z, Zhao B, Zhao T, Cai X, Chen J (2024) An adaptive differential evolution algorithm based on archive reuse. Inf Sci 668:120524","journal-title":"Inf Sci"},{"issue":"6","key":"2556_CR6","doi-asserted-by":"publisher","first-page":"3954","DOI":"10.1109\/TSMC.2019.2956121","volume":"51","author":"S Gao","year":"2019","unstructured":"Gao S, Yu Y, Wang Y, Wang J, Cheng J, Zhou M (2019) Chaotic local search-based differential evolution algorithms for optimization. IEEE Trans Syst Man Cybern Syst 51(6):3954\u20133967","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"2556_CR7","doi-asserted-by":"publisher","first-page":"102","DOI":"10.3389\/fbuil.2020.00102","volume":"6","author":"M Georgioudakis","year":"2020","unstructured":"Georgioudakis M, Plevris V (2020) A comparative study of differential evolution variants in constrained structural optimization. Front Built Environ 6:102","journal-title":"Front Built Environ"},{"key":"2556_CR8","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/s40747-018-0086-8","volume":"5","author":"AA Hadi","year":"2019","unstructured":"Hadi AA, Mohamed AW, Jambi KM (2019) LSHADE-SPA memetic framework for solving large-scale optimization problems. Complex Intell Syst 5:25\u201340","journal-title":"Complex Intell Syst"},{"key":"2556_CR9","doi-asserted-by":"crossref","unstructured":"Hadi A.A, Mohamed A.W, Jambi K.M (2021). Single-objective real-parameter optimization: Enhanced LSHADE-SPACMA algorithm. Heuristics for optimization and learning, pp.103-121","DOI":"10.1007\/978-3-030-58930-1_7"},{"issue":"1","key":"2556_CR10","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1080\/10556788.2020.1808977","volume":"36","author":"N Hansen","year":"2021","unstructured":"Hansen N, Auger A, Ros R, Mersmann O, Tu\u0161ar T, Brockhoff D (2021) COCO: a platform for comparing continuous optimizers in a black-box setting. Optim Methods Softw 36(1):114\u2013144","journal-title":"Optim Methods Softw"},{"key":"2556_CR11","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1007\/s10489-023-05038-w","volume":"54","author":"P Jin","year":"2024","unstructured":"Jin P, Cen J, Feng Q et al (2024) Differential evolution with the mutation strategy transformation based on a quartile for numerical optimization. Appl Intell 54:334\u2013356. https:\/\/doi.org\/10.1007\/s10489-023-05038-w","journal-title":"Appl Intell"},{"key":"2556_CR12","doi-asserted-by":"crossref","unstructured":"Kumar P, Garg V (2023) Advanced Selection Operation for Differential Evolution Algorithm. Design and Applications of Nature Inspired Optimization: Contribution of Women Leaders in the Field. Springer International Publishing, Cham, pp 55\u201374","DOI":"10.1007\/978-3-031-17929-7_4"},{"key":"2556_CR13","doi-asserted-by":"publisher","unstructured":"Kumar A, Misra R.K, Singh D (2017), June. Improving the local search capability of effective butterfly optimizer using covariance matrix adapted retreat phase. In 2017 IEEE congress on evolutionary computation (CEC) (pp. 1835-1842). IEEE. https:\/\/doi.org\/10.1109\/CEC.2017.7969524.","DOI":"10.1109\/CEC.2017.7969524."},{"key":"2556_CR14","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1016\/j.asoc.2016.06.011","volume":"47","author":"G Li","year":"2016","unstructured":"Li G, Lin Q, Cui L, Du Z, Liang Z, Chen J, Lu N, Ming Z (2016) A novel hybrid differential evolution algorithm with modified CoDE and JADE. Appl Soft Comput 47:577\u2013599","journal-title":"Appl Soft Comput"},{"key":"2556_CR15","unstructured":"Li J.Y, Du K.J, Zhan Z.H, Wang H, Zhang J (2022). Distributed differential evolution with adaptive resource allocation. IEEE transactions on cybernetics"},{"key":"2556_CR16","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.cie.2015.04.012","volume":"85","author":"AW Mohamed","year":"2015","unstructured":"Mohamed AW (2015) An improved differential evolution algorithm with triangular mutation for global numerical optimization. Comput Ind Eng 85:359\u2013375","journal-title":"Comput Ind Eng"},{"key":"2556_CR17","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1007\/s10845-017-1294-6","volume":"29","author":"AW Mohamed","year":"2018","unstructured":"Mohamed AW (2018) A novel differential evolution algorithm for solving constrained engineering optimization problems. J Intell Manuf 29:659\u2013692","journal-title":"J Intell Manuf"},{"key":"2556_CR18","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/s13042-017-0711-7","volume":"10","author":"AW Mohamed","year":"2019","unstructured":"Mohamed AW, Mohamed AK (2019) Adaptive guided differential evolution algorithm with novel mutation for numerical optimization. Int J Mach Learn Cybern 10:253\u2013277","journal-title":"Int J Mach Learn Cybern"},{"issue":"2","key":"2556_CR19","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.jare.2011.06.004","volume":"3","author":"AW Mohamed","year":"2012","unstructured":"Mohamed AW, Sabry HZ, Khorshid M (2012) An alternative differential evolution algorithm for global optimization. J Adv Res 3(2):149\u2013165","journal-title":"J Adv Res"},{"issue":"1","key":"2556_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/IJAMC.2019010101","volume":"10","author":"AW Mohamed","year":"2019","unstructured":"Mohamed AW, Mohamed AK, Elfeky EZ, Saleh M (2019) Enhanced directed differential evolution algorithm for solving constrained engineering optimization problems. Int J Appl Metaheur Comput (IJAMC) 10(1):1\u201328","journal-title":"Int J Appl Metaheur Comput (IJAMC)"},{"key":"2556_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2018.10.006","volume":"50","author":"AW Mohamed","year":"2019","unstructured":"Mohamed AW, Hadi AA, Jambi KM (2019) Novel mutation strategy for enhancing SHADE and LSHADE algorithms for global numerical optimization. Swarm Evolut Comput 50:100455","journal-title":"Swarm Evolut Comput"},{"issue":"7","key":"2556_CR22","doi-asserted-by":"publisher","first-page":"1501","DOI":"10.1007\/s13042-019-01053-x","volume":"11","author":"AW Mohamed","year":"2020","unstructured":"Mohamed AW, Hadi AA, Mohamed AK (2020) Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm. Int J Mach Learn Cybern 11(7):1501\u20131529","journal-title":"Int J Mach Learn Cybern"},{"key":"2556_CR23","doi-asserted-by":"publisher","unstructured":"Mohamed A. W, Hadi A. A, Fattouh A. M, Jambi K. M (2017) \u2018LSHADE with semi-parameter adaptation hybrid with CMA-ES for solving CEC 2017 benchmark problems,\u2019 in Proc. IEEE Congr. Evol. Comput. (CEC), Jun. pp. 145-152, https:\/\/doi.org\/10.1109\/CEC.2017.7969307","DOI":"10.1109\/CEC.2017."},{"key":"2556_CR24","doi-asserted-by":"crossref","unstructured":"Mohamed A.W, Hadi A.A, Mohamed A.K, Awad N.H (2020), July. Evaluating the performance of adaptive gainingsharing knowledge based algorithm on CEC 2020 benchmark problems. In 2020 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE","DOI":"10.1109\/CEC48606.2020.9185901"},{"key":"2556_CR25","doi-asserted-by":"crossref","unstructured":"Mohamed A.K, Hadi A.A, Mohamed A.W (2020) October. Generalized adaptive differential evolution algorithm for solving CEC 2020 benchmark problems. In 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) (pp. 391-396). IEEE","DOI":"10.1109\/NILES50944.2020.9257924"},{"key":"2556_CR26","doi-asserted-by":"crossref","unstructured":"Nguyen D.M (2022), July. Benchmarking some variants of the CMAES-APOP using keeping search points and mirrored sampling combined with active CMA on the BBOB noiseless testbed. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1734-1742)","DOI":"10.1145\/3520304.3534001"},{"key":"2556_CR27","doi-asserted-by":"crossref","unstructured":"Nishida K, Akimoto Y, (2016), July. Evaluating the population size adaptation mechanism for CMA-ES on the BBOB noiseless testbed. In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion (pp. 1185-1192)","DOI":"10.1145\/2908961.2931700"},{"key":"2556_CR28","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.swevo.2018.03.007","volume":"43","author":"AP Piotrowski","year":"2018","unstructured":"Piotrowski AP, Napiorkowski JJ (2018) Step-by-step improvement of JADE and SHADE-based algorithms: success or failure? Swarm Evolut Comput 43:88\u2013108","journal-title":"Swarm Evolut Comput"},{"key":"2556_CR29","doi-asserted-by":"publisher","first-page":"2005","DOI":"10.1007\/s11276-016-1270-7","volume":"23","author":"PS Rao","year":"2017","unstructured":"Rao PS, Jana PK, Banka H (2017) A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks. Wirel Netw 23:2005\u20132020","journal-title":"Wirel Netw"},{"issue":"4","key":"2556_CR30","doi-asserted-by":"publisher","first-page":"389","DOI":"10.3233\/IDT-180343","volume":"12","author":"SP Singh","year":"2018","unstructured":"Singh SP (2018) New adaption based mutation operator on differential evolution algorithm. Intell Decis Technol 12(4):389\u2013397. https:\/\/doi.org\/10.3233\/IDT-180343","journal-title":"Intell Decis Technol"},{"issue":"5","key":"2556_CR31","doi-asserted-by":"publisher","first-page":"3525","DOI":"10.3233\/JIFS-169289","volume":"32","author":"SP Singh","year":"2017","unstructured":"Singh SP, Kumar A (2017) Homeostasis mutation based differential evolution algorithm. J Intell Fuzzy Syst 32(5):3525\u20133537","journal-title":"J Intell Fuzzy Syst"},{"issue":"5","key":"2556_CR32","doi-asserted-by":"publisher","first-page":"3245","DOI":"10.3233\/JIFS-169268","volume":"32","author":"SP Singh","year":"2017","unstructured":"Singh SP, Kumar A (2017) Pareto based differential evolution with homeostasis based mutation. J Intell Fuzzy Syst 32(5):3245\u20133257","journal-title":"J Intell Fuzzy Syst"},{"key":"2556_CR33","doi-asserted-by":"publisher","first-page":"628","DOI":"10.1007\/s10489-017-0980-6","volume":"48","author":"SP Singh","year":"2018","unstructured":"Singh SP, Kumar A (2018) Multiobjective differential evolution using homeostasis based mutation for application in software cost estimation. Appl Intell 48:628\u2013650","journal-title":"Appl Intell"},{"issue":"6","key":"2556_CR34","first-page":"740","volume":"33","author":"SP Singh","year":"2021","unstructured":"Singh SP, Singh VP, Mehta AK (2021) Differential evolution using homeostasis adaption based mutation operator and its application for software cost estimation. J King Saud Univ Comput Inf Sci 33(6):740\u2013752","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"2556_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107981","volume":"113","author":"SP Singh","year":"2021","unstructured":"Singh SP, Dhiman G, Tiwari P, Jhaveri RH (2021) A soft computing based multi-objective optimization approach for automatic prediction of software cost models. Appl Soft Comput 113:107981","journal-title":"Appl Soft Comput"},{"key":"2556_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.phycom.2022.101893","volume":"55","author":"SP Singh","year":"2022","unstructured":"Singh SP, Viriyasitavat W, Juneja S, Alshahrani H, Shaikh A, Dhiman G, Singh A, Kaur A (2022) Dual adaption based evolutionary algorithm for optimized the smart healthcare communication service of the internet of things in smart city. Phys Commun 55:101893","journal-title":"Phys Commun"},{"key":"2556_CR37","doi-asserted-by":"crossref","unstructured":"Singh S.P, Kumar A (2017), January. Software cost estimation using homeostasis mutation based differential evolution. In 2017 11th International Conference on Intelligent Systems and Control (ISCO) (pp. 173-181). IEEE","DOI":"10.1109\/ISCO.2017.7855976"},{"key":"2556_CR38","doi-asserted-by":"publisher","unstructured":"Singh S.P, Kumar A (2017). Differential evolution algorithm using population-based homeostasis difference vector. In Advances in Computer and Computational Sciences: Proceedings of ICCCCS 2016, Volume 1 (pp. 579-587). Springer Singapore. https:\/\/doi.org\/10.1007\/978-981-10-3770-2_54","DOI":"10.1007\/978-981-10-3770-2_54"},{"key":"2556_CR39","unstructured":"Storn R (1995) Differrential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical report, International Computer Science Institute, p 11"},{"key":"2556_CR40","doi-asserted-by":"crossref","unstructured":"Tan M, Li Y, Ding D, Zhou,R., Huang C (2022). An Improved JADE Hybridizing with Tuna Swarm Optimization for Numerical Optimization Problems. Mathematical Problems in Engineering, 2022","DOI":"10.1155\/2022\/7726548"},{"key":"2556_CR41","doi-asserted-by":"crossref","unstructured":"Tu\u0161ar T, Brockhoff D, Hansen N (2019), July. Mixed-integer benchmark problems for single-and bi-objective optimization. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 718-726)","DOI":"10.1145\/3321707.3321868"},{"issue":"12","key":"2556_CR42","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MCOM.2016.1600399CM","volume":"54","author":"K Wang","year":"2016","unstructured":"Wang K, Wang Y, Sun Y, Guo S, Wu J (2016) Green industrial internet of things architecture: an energy-efficient perspective. IEEE Commun Mag 54(12):48\u201354","journal-title":"IEEE Commun Mag"},{"key":"2556_CR43","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.asoc.2016.07.012","volume":"48","author":"Y Wang","year":"2016","unstructured":"Wang Y, Liu ZZ, Li J, Li HX, Yen GG (2016) Utilizing cumulative population distribution information in differential evolution. Appl Soft Comput 48:329\u2013346","journal-title":"Appl Soft Comput"},{"issue":"5","key":"2556_CR44","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1109\/TEVC.2017.2669098","volume":"21","author":"Y Wang","year":"2017","unstructured":"Wang Y, Xu B, Sun G, Yang S (2017) A two-phase differential evolution for uniform designs in constrained experimental domains. IEEE Trans Evolut Comput 21(5):665\u2013680. https:\/\/doi.org\/10.1109\/TEVC.2017.2669098","journal-title":"IEEE Trans Evolut Comput"},{"key":"2556_CR45","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.ins.2015.09.009","volume":"329","author":"G Wu","year":"2016","unstructured":"Wu G, Mallipeddi R, Suganthan PN, Wang R, Chen H (2016) Differential evolution with multi-population based ensemble of mutation strategies. Inf Sci 329:329\u2013345","journal-title":"Inf Sci"},{"key":"2556_CR46","doi-asserted-by":"crossref","unstructured":"Wu G, Shen X, Li H, Chen H, Lin A, Suganthan PN (2018) Ensemble of differential evolution variants. Inf Sci 423:172\u2013186","DOI":"10.1016\/j.ins.2017.09.053"},{"key":"2556_CR47","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.ins.2022.10.111","volume":"617","author":"Z Zeng","year":"2022","unstructured":"Zeng Z, Zhang H (2022) An evolutionary-state-based selection strategy for enhancing differential evolution algorithm. Inf Sci 617:373\u2013394","journal-title":"Inf Sci"},{"issue":"21","key":"2556_CR48","doi-asserted-by":"publisher","first-page":"13595","DOI":"10.1007\/s00500-021-06077-6","volume":"25","author":"M Zuo","year":"2021","unstructured":"Zuo M, Dai G, Peng L (2021) A new mutation operator for differential evolution algorithm. Soft Comput 25(21):13595\u201313615","journal-title":"Soft Comput"}],"container-title":["International Journal of System Assurance Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02556-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13198-024-02556-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02556-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T19:03:54Z","timestamp":1732129434000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13198-024-02556-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":48,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["2556"],"URL":"https:\/\/doi.org\/10.1007\/s13198-024-02556-9","relation":{},"ISSN":["0975-6809","0976-4348"],"issn-type":[{"value":"0975-6809","type":"print"},{"value":"0976-4348","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"13 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 October 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This declaration is not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}