The increasing numbers of design variables and constraints have made many construction-engineering problems significantly more complex and difficult for engineers to resolve in a timely manner. Various optimization models have been developed to address this problem. The present paper introduces Symbiotic Organisms Search (SOS), a novel metaheuristic algorithm for solving construction-engineering problems. SOS simulates mutualism, commensalism, and parasitism, which are the symbiotic interaction mechanisms that organisms often adopt for survival in the ecosystem. The proposed algorithm is compared with other algorithms recently developed with regard their respective effectiveness in solving benchmark problems and three construction-engineering problems. Simulation results demonstrate that the proposed SOS algorithm is significantly more effective and efficient than the other algorithms tested. Therefore, the proposed model is a promising tool for assisting construction-engineering decision makers to make decisions that minimize the expenditure of material and financial resources.

The increasing numbers of design variables and constraints have made many construction-engineering problems significantly more complex and difficult for engineers to resolve in a timely manner. Various optimization models have been developed to address this problem. The present paper introduces Symbiotic Organisms Search (SOS), a novel metaheuristic algorithm for solving construction-engineering problems. SOS simulates mutualism, commensalism, and parasitism, which are the symbiotic interaction mechanisms that organisms often adopt for survival in the ecosystem. The proposed algorithm is compared with other algorithms recently developed with regard their respective effectiveness in solving benchmark problems and three construction-engineering problems. Simulation results demonstrate that the proposed SOS algorithm is significantly more effective and efficient than the other algorithms tested. Therefore, the proposed model is a promising tool for assisting construction-engineering decision makers to make decisions that minimize the expenditure of material and financial resources.

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