Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems
This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where eva...
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| Other Authors: | , , , , |
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2022
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| Online Access: | https://depot.sorbonne.ae/handle/20.500.12458/1338 |
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| _version_ | 1857415062682075136 |
|---|---|
| author | Agushaka, Jeffrey O. |
| author2 | Ezugwu, Absalom E. Olaide, Oyelade N. Akinola, Olatunji Abu Zitar, Raed Abualigah, Laith |
| author2_role | author author author author author |
| author_facet | Agushaka, Jeffrey O. Ezugwu, Absalom E. Olaide, Oyelade N. Akinola, Olatunji Abu Zitar, Raed Abualigah, Laith |
| author_role | author |
| dc.creator.none.fl_str_mv | Agushaka, Jeffrey O. Ezugwu, Absalom E. Olaide, Oyelade N. Akinola, Olatunji Abu Zitar, Raed Abualigah, Laith |
| dc.date.none.fl_str_mv | 2022-12-14T09:49:47Z 2022-12-14T09:49:47Z 2023 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 10.1007/s42235-022-00316-8 1672-6529 2543-2141 https://depot.sorbonne.ae/handle/20.500.12458/1338 10.1007/s42235-022-00316-8 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Journal of Bionic Engineering |
| dc.subject.none.fl_str_mv | Improved dwarf mongoose Nature-inspired algorithms Constrained optimization Unconstrained optimization Engineering design problems |
| dc.title.none.fl_str_mv | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms. |
| id | sorbonner_3cc11aebd8a0932a2a411d29e71e4787 |
| identifier_str_mv | 10.1007/s42235-022-00316-8 1672-6529 2543-2141 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1338 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Improved Dwarf Mongoose Optimization for Constrained Engineering Design ProblemsAgushaka, Jeffrey O.Ezugwu, Absalom E.Olaide, Oyelade N.Akinola, OlatunjiAbu Zitar, RaedAbualigah, LaithImproved dwarf mongooseNature-inspired algorithmsConstrained optimizationUnconstrained optimizationEngineering design problemsThis paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.2022-12-14T09:49:47Z2022-12-14T09:49:47Z2023Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal articleapplication/pdf10.1007/s42235-022-00316-81672-65292543-2141https://depot.sorbonne.ae/handle/20.500.12458/133810.1007/s42235-022-00316-8enJournal of Bionic Engineeringoai:depot.sorbonne.ae:20.500.12458/13382024-03-11T07:27:25Z |
| spellingShingle | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems Agushaka, Jeffrey O. Improved dwarf mongoose Nature-inspired algorithms Constrained optimization Unconstrained optimization Engineering design problems |
| title | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| title_full | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| title_fullStr | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| title_full_unstemmed | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| title_short | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| title_sort | Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems |
| topic | Improved dwarf mongoose Nature-inspired algorithms Constrained optimization Unconstrained optimization Engineering design problems |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1338 |