Abstract: Optimizing silencer placement in Heating, Ventilation, and Air Conditioning (HVAC) systems is a complex multi-objective problem due to conflicting objectives (noise, energy, cost) and intricate topological constraints. Conventional Multi-Objective Evolutionary Algorithms (MOEAs) often exhibit inefficient convergence on such problems due to their reliance on random search strategies. Addressing this challenging HVAC design problem requires a more informed approach. This paper proposes the G-HNSGA-III (Graph-Informed Hybrid NSGA-III), a novel framework that enhances the NSGA-III algorithm by embedding domain-specific knowledge from the system's Directed Acyclic Graph (DAG) topology. This is achieved through two core components that leverage heuristic search: a Graph-Informed Initialization (GINI) strategy to provide a high-quality starting population and a Graph-Informed Local Search (GILS) module for post-processing refinement. The performance of G-HNSGA-III was comprehensively benchmarked against the baseline NSGA-III and six other established MOEAs on a complex data center test instance. The results demonstrate a marked superiority, with G-HNSGA-III achieving a 38.4% higher mean Hypervolume (HV) than the baseline NSGA-III and a 99.3% Set Coverage (SC) dominance over MOEA/D. The framework consistently converged to the best-known Pareto front, achieving a final mean Inverted Generational Distance (IGD) of 0.0030. These findings validate that the proposed graph-informed strategies effectively accelerate convergence and enable the discovery of a higher-quality Pareto front, providing superior and practically applicable solutions for complex engineering design problems.

Xiangming Liu, Bin Liu, Kunze Du, Da Gao and Nan Li. “Multi-Objective Design Optimization of Ventilation Duct Systems: A Graph-Informed Hybrid Evolutionary Approach”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.12 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161250

@article{Liu2025,
title = {Multi-Objective Design Optimization of Ventilation Duct Systems: A Graph-Informed Hybrid Evolutionary Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161250},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161250},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {12},
author = {Xiangming Liu and Bin Liu and Kunze Du and Da Gao and Nan Li}
}