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Abstract
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This research introduces a novel metaheuristic approach called the Discrete Integer Metaheuristic Optimiza- tion Algorithm to enhance the ef i ciency of truss optimization processes involving discrete size variables and integer values. The proposed algorithm employs two distinct search scenarios: randomized exploration within plus-minus 10% of the leader point, and point-centric search with dynamic perturbation controlled by a Diver- sity Enhancement Parameter. The ef f ectiveness of the proposed algorithm was evaluated on three benchmark truss optimization problems: a planar truss with 45 members, a space truss consisting of 198 elements, and a 160-bar space truss. The obtained results demonstrate that the proposed algorithm demonstrates improved per- formance, achieving average weight reductions of 15.3%, 21.2%, and 8.4% compared to the Marine Predators Algorithm, Whale Optimization Algorithm, and Enhanced Vibrating Particles System respectively for the three test cases. The algorithm also shows faster convergence, requiring 32% fewer iterations on average to reach optimal solutions. These results highlight the proposed algorithm’s potential for advancing truss optimization techniques in engineering applications involving discrete and integer variables, leading to more ef i cient and economical structural designs.
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