Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity Article Swipe
Divya Adalja
,
Kanak Kalita
,
Lenka Čepová
,
Pinank Patel
,
Nikunj Mashru
,
Pradeep Jangir
,
Arpita Arpita
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rineng.2025.104241
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rineng.2025.104241
The challenge of achieving equilibrium between exploration and exploitation stands as a critical barrier in multi-objective metaheuristic optimization when applied to complex engineering problems such as truss structure design. The Multi-Objective Weighted Average Algorithm (MOWAA) presents a new methodology which employs adaptive weighted average position control to optimize population movement for enhanced solution quality. The performance evaluation of MOWAA relies on benchmarking it against five state-of-the-art multi-objective optimization algorithms NSGA-II, MOEA/D, MOLCA, MOEDO and MORIME through eight truss structure optimization problems of increasing complexity. The evaluation of performance relies on three key metrics: Hypervolume (HV), Inverted Generational Distance (IGD) and Spacing (SP). MOWAA demonstrates superior performance compared to competing algorithms through its ability to generate Pareto fronts with higher HV values and lower IGD values and more uniform distribution. The enhanced performance of MOWAA demonstrates its superior capability to efficiently explore the objective space for finding optimal weight-minimization and compliance trade-offs. The robustness of MOWAA is proven through statistical validation with the Friedman rank test which establishes MOWAA as the leading approach with statistically significant advantages. MOWAA demonstrates runtime efficiency throughout truss optimization tasks of varying sizes which enables its practical application for real-world structural optimization problems. MOWAA emerges as a sophisticated and efficient optimization method which demonstrates strong capabilities for engineering applications and computational design.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.rineng.2025.104241
- OA Status
- gold
- Cited By
- 44
- References
- 26
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407365448Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.rineng.2025.104241Digital Object Identifier
- Title
-
Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversityWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
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2025-02-11Full publication date if available
- Authors
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Divya Adalja, Kanak Kalita, Lenka Čepová, Pinank Patel, Nikunj Mashru, Pradeep Jangir, Arpita ArpitaList of authors in order
- Landing page
-
https://doi.org/10.1016/j.rineng.2025.104241Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.rineng.2025.104241Direct OA link when available
- Concepts
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Truss, Convergence (economics), Diversity (politics), Mathematical optimization, Algorithm, Optimization algorithm, Computer science, Mathematics, Structural engineering, Engineering, Economics, Sociology, Anthropology, Economic growthTop concepts (fields/topics) attached by OpenAlex
- Cited by
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44Total citation count in OpenAlex
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2025: 44Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.MOEA/D, | 70 |
| abstract_inverted_index.Spacing | 100 |
| abstract_inverted_index.ability | 112 |
| abstract_inverted_index.against | 63 |
| abstract_inverted_index.applied | 19 |
| abstract_inverted_index.average | 43 |
| abstract_inverted_index.barrier | 13 |
| abstract_inverted_index.between | 5 |
| abstract_inverted_index.complex | 21 |
| abstract_inverted_index.control | 45 |
| abstract_inverted_index.design. | 28, 215 |
| abstract_inverted_index.emerges | 198 |
| abstract_inverted_index.employs | 40 |
| abstract_inverted_index.enables | 188 |
| abstract_inverted_index.explore | 140 |
| abstract_inverted_index.finding | 145 |
| abstract_inverted_index.leading | 170 |
| abstract_inverted_index.optimal | 146 |
| abstract_inverted_index.runtime | 178 |
| abstract_inverted_index.through | 75, 110, 157 |
| abstract_inverted_index.uniform | 127 |
| abstract_inverted_index.varying | 185 |
| abstract_inverted_index.Distance | 97 |
| abstract_inverted_index.Friedman | 162 |
| abstract_inverted_index.Inverted | 95 |
| abstract_inverted_index.NSGA-II, | 69 |
| abstract_inverted_index.Weighted | 31 |
| abstract_inverted_index.adaptive | 41 |
| abstract_inverted_index.approach | 171 |
| abstract_inverted_index.compared | 106 |
| abstract_inverted_index.critical | 12 |
| abstract_inverted_index.enhanced | 51, 130 |
| abstract_inverted_index.generate | 114 |
| abstract_inverted_index.metrics: | 92 |
| abstract_inverted_index.movement | 49 |
| abstract_inverted_index.optimize | 47 |
| abstract_inverted_index.position | 44 |
| abstract_inverted_index.presents | 35 |
| abstract_inverted_index.problems | 23, 80 |
| abstract_inverted_index.quality. | 53 |
| abstract_inverted_index.solution | 52 |
| abstract_inverted_index.superior | 104, 136 |
| abstract_inverted_index.weighted | 42 |
| abstract_inverted_index.Algorithm | 33 |
| abstract_inverted_index.achieving | 3 |
| abstract_inverted_index.challenge | 1 |
| abstract_inverted_index.competing | 108 |
| abstract_inverted_index.efficient | 203 |
| abstract_inverted_index.objective | 142 |
| abstract_inverted_index.practical | 190 |
| abstract_inverted_index.problems. | 196 |
| abstract_inverted_index.structure | 27, 78 |
| abstract_inverted_index.algorithms | 68, 109 |
| abstract_inverted_index.capability | 137 |
| abstract_inverted_index.compliance | 149 |
| abstract_inverted_index.efficiency | 179 |
| abstract_inverted_index.evaluation | 56, 85 |
| abstract_inverted_index.increasing | 82 |
| abstract_inverted_index.population | 48 |
| abstract_inverted_index.real-world | 193 |
| abstract_inverted_index.robustness | 152 |
| abstract_inverted_index.structural | 194 |
| abstract_inverted_index.throughout | 180 |
| abstract_inverted_index.validation | 159 |
| abstract_inverted_index.Hypervolume | 93 |
| abstract_inverted_index.advantages. | 175 |
| abstract_inverted_index.application | 191 |
| abstract_inverted_index.complexity. | 83 |
| abstract_inverted_index.efficiently | 139 |
| abstract_inverted_index.engineering | 22, 211 |
| abstract_inverted_index.equilibrium | 4 |
| abstract_inverted_index.establishes | 166 |
| abstract_inverted_index.exploration | 6 |
| abstract_inverted_index.methodology | 38 |
| abstract_inverted_index.performance | 55, 87, 105, 131 |
| abstract_inverted_index.significant | 174 |
| abstract_inverted_index.statistical | 158 |
| abstract_inverted_index.trade-offs. | 150 |
| abstract_inverted_index.Generational | 96 |
| abstract_inverted_index.applications | 212 |
| abstract_inverted_index.benchmarking | 61 |
| abstract_inverted_index.capabilities | 209 |
| abstract_inverted_index.demonstrates | 103, 134, 177, 207 |
| abstract_inverted_index.exploitation | 8 |
| abstract_inverted_index.optimization | 17, 67, 79, 182, 195, 204 |
| abstract_inverted_index.computational | 214 |
| abstract_inverted_index.distribution. | 128 |
| abstract_inverted_index.metaheuristic | 16 |
| abstract_inverted_index.sophisticated | 201 |
| abstract_inverted_index.statistically | 173 |
| abstract_inverted_index.Multi-Objective | 30 |
| abstract_inverted_index.multi-objective | 15, 66 |
| abstract_inverted_index.state-of-the-art | 65 |
| abstract_inverted_index.weight-minimization | 147 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile.value | 0.99970365 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |