MOPDO: a multi-objective prairie dog optimizer for engineering design problems

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dc.authoridjangir, pradeep/0000-0001-6944-4775
dc.authoridTejani, Ghanshyam/0000-0001-9106-0313
dc.contributor.authorTejani, Ghanshyam G.
dc.contributor.authorKumar, Sumit
dc.contributor.authorMehta, Pranav
dc.contributor.authorJangir, Pradeep
dc.contributor.authorCelik, Emre
dc.date.accessioned2025-10-11T20:48:44Z
dc.date.available2025-10-11T20:48:44Z
dc.date.issued2025
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThis research introduces a novel multi-objective version of the recently proposed prairie dog optimizer, the multi-objective prairie dog optimizer (MOPDO). Inspired by the foraging and burrowing activities of prairie dogs, which entail search exploration and particular responses to distinctive alarms for exploitation, MOPDO is proposed. This is a Pareto dominance-based approach to a modified and enhanced version of its single objective counterpart. MOPDO is able to deal with multiple objectives, explore, and exploit promising regions in the optimization landscape, and identify non-dominated solutions, providing decision makers with valuable trade-off choices. To demonstrate its practical applicability, MOPDO is applied to tackle five challenging structural design problems, each characterized by two conflicting objectives: two objectives, minimizing structure weight and minimizing maximum nodal displacement. The algorithm is compared against two other state-of-the-art multi-objective algorithms and rigorous evaluation is conducted using Hypervolume testing. The results show that MOPDO performs better than the comparison algorithms and is able to find a diverse set of non-dominated solutions. Statistical analysis of the experimental results using Friedman's rank test is conducted to further investigate the experimental results. MOPDO's solutions and convergence behaviour show that MOPDO is a very efficient method to solve complex design problems and is superior to the existing multi-objective algorithms in terms of effectiveness and efficiency.en_US
dc.identifier.doi10.1007/s12008-025-02280-z
dc.identifier.issn1955-2513
dc.identifier.issn1955-2505
dc.identifier.scopus2-s2.0-105004445696en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s12008-025-02280-z
dc.identifier.urihttps://hdl.handle.net/20.500.12684/22051
dc.identifier.wosWOS:001483856700001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofInternational Journal of Interactive Designand Manufacturing - Ijidemen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250911
dc.subjectMulti-objectiveen_US
dc.subjectTruss designen_US
dc.subjectComputational analysisen_US
dc.subjectExploitationen_US
dc.subjectExplorationen_US
dc.subjectConstraints techniquesen_US
dc.titleMOPDO: a multi-objective prairie dog optimizer for engineering design problemsen_US
dc.typeArticleen_US

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