FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3098554554> ?p ?o ?g. }

• W3098554554 endingPage "106903" @default.
• W3098554554 startingPage "106903" @default.
• W3098554554 abstract "This article presents two new hybrid swarm-human based meta-heuristic optimization algorithms benefitting from the synergy of whale optimization algorithm (WOA) and social group optimization (SGO) known as Hybrid Social Whale Optimization Algorithm (HS-WOA and HS-WOA+). HS-WOA and HS-WOA+ are hybridized combining the exploratory capabilities of WOA and convergence capabilities of SGO with a perfect balance between exploration and exploitation. A comparative analysis of the new proposed hybrid algorithm is performed through various benchmark functions. Various test cases to analyze the algorithm’s performance like influence of population size, effect of dimensionality, effect of iterative count is performed and compared. The proposed algorithms are compared with modern-meta-heuristics and variants of WOA and SGO to justify its performance. The performance is evaluated statistically through the Wilcoxon’s rank-sum test and Friedman’s non-parametric test while the convergence curves and acceleration rates are provided to demonstrate the convergence capabilities of the proposed hybrid algorithms and the computational times are recorded to showcase the computational speeds of all the algorithms used in comparison. Composite benchmarking functions are considered to analyze the exploratory prowess and the algorithms’ capability to avoid local entrapment. To assess and evaluate the performance of the proposed algorithms with real world optimization tasks, four standard engineering problems with penalty constraints are added to the test bench. Further, a multi-unit production planning problem with correction constraints is deployed through the proposed algorithms. The benchmarking results prove that HS-WOA and HS-WOA+ s’ performance is competitive and better than the various algorithms tested against and had a statistically significant performance with lower computational times. The algorithms performed well for both standard engineering problems and the multi-unit production planning problem outperforming the various algorithms in the literature." @default.
• W3098554554 created "2020-11-23" @default.
• W3098554554 creator A5000161177 @default.
• W3098554554 creator A5081582339 @default.
• W3098554554 date "2021-02-01" @default.
• W3098554554 modified "2023-10-04" @default.
• W3098554554 title "A combinatorial social group whale optimization algorithm for numerical and engineering optimization problems" @default.
• W3098554554 cites W1982147649 @default.
• W3098554554 cites W1984345688 @default.
• W3098554554 cites W1985460844 @default.
• W3098554554 cites W1993885071 @default.
• W3098554554 cites W1994272857 @default.
• W3098554554 cites W1994867044 @default.
• W3098554554 cites W1999284878 @default.
• W3098554554 cites W2011890778 @default.
• W3098554554 cites W2012162805 @default.
• W3098554554 cites W2025122100 @default.
• W3098554554 cites W2039685918 @default.
• W3098554554 cites W2040821333 @default.
• W3098554554 cites W2045239993 @default.
• W3098554554 cites W2050375132 @default.
• W3098554554 cites W2050546928 @default.
• W3098554554 cites W2053313434 @default.
• W3098554554 cites W2055735915 @default.
• W3098554554 cites W2056050857 @default.
• W3098554554 cites W2061438946 @default.
• W3098554554 cites W2074627161 @default.
• W3098554554 cites W2085423687 @default.
• W3098554554 cites W2151554678 @default.
• W3098554554 cites W2156194072 @default.
• W3098554554 cites W2159427933 @default.
• W3098554554 cites W2169209574 @default.
• W3098554554 cites W2169245194 @default.
• W3098554554 cites W2171830216 @default.
• W3098554554 cites W219883171 @default.
• W3098554554 cites W2290883490 @default.
• W3098554554 cites W2306115793 @default.
• W3098554554 cites W2416614998 @default.
• W3098554554 cites W2502171795 @default.
• W3098554554 cites W2511284938 @default.
• W3098554554 cites W2542691202 @default.
• W3098554554 cites W2554679694 @default.
• W3098554554 cites W2594056497 @default.
• W3098554554 cites W2612473079 @default.
• W3098554554 cites W2613613071 @default.
• W3098554554 cites W2618294030 @default.
• W3098554554 cites W2738900493 @default.
• W3098554554 cites W2762451727 @default.
• W3098554554 cites W2767846463 @default.
• W3098554554 cites W2790662215 @default.
• W3098554554 cites W2790763152 @default.
• W3098554554 cites W2791899797 @default.
• W3098554554 cites W2792378075 @default.
• W3098554554 cites W2797485770 @default.
• W3098554554 cites W2803364900 @default.
• W3098554554 cites W2803599323 @default.
• W3098554554 cites W2807897186 @default.
• W3098554554 cites W2809430074 @default.
• W3098554554 cites W2883342565 @default.
• W3098554554 cites W2886499297 @default.
• W3098554554 cites W2887171350 @default.
• W3098554554 cites W2888248957 @default.
• W3098554554 cites W2900164475 @default.
• W3098554554 cites W2902067542 @default.
• W3098554554 cites W2905366447 @default.
• W3098554554 cites W2912733464 @default.
• W3098554554 cites W2914242080 @default.
• W3098554554 cites W2922096023 @default.
• W3098554554 cites W2922792316 @default.
• W3098554554 cites W2923345427 @default.
• W3098554554 cites W2929255206 @default.
• W3098554554 cites W2943528199 @default.
• W3098554554 cites W2945388506 @default.
• W3098554554 cites W2956155297 @default.
• W3098554554 cites W2958456210 @default.
• W3098554554 cites W2963103847 @default.
• W3098554554 cites W2990991805 @default.
• W3098554554 cites W2992826765 @default.
• W3098554554 cites W3007040893 @default.
• W3098554554 cites W3014974411 @default.
• W3098554554 cites W3025548389 @default.
• W3098554554 cites W3042764400 @default.
• W3098554554 cites W50145612 @default.
• W3098554554 cites W883434633 @default.
• W3098554554 doi "https://doi.org/10.1016/j.asoc.2020.106903" @default.
• W3098554554 hasPublicationYear "2021" @default.
• W3098554554 type Work @default.
• W3098554554 sameAs 3098554554 @default.
• W3098554554 citedByCount "25" @default.
• W3098554554 countsByYear W30985545542021 @default.
• W3098554554 countsByYear W30985545542022 @default.
• W3098554554 countsByYear W30985545542023 @default.
• W3098554554 crossrefType "journal-article" @default.
• W3098554554 hasAuthorship W3098554554A5000161177 @default.
• W3098554554 hasAuthorship W3098554554A5081582339 @default.
• W3098554554 hasConcept C105795698 @default.
• W3098554554 hasConcept C11413529 @default.
• W3098554554 hasConcept C122357587 @default.

• next