Journal of Engineering, Project, and Production Management, 2026, 16(3), 2025-202
Optimization of Municipal Construction Project Management Using Multi-Objective IGA
Associate Senior Engineer, Hangzhou Qiantang Urban Construction Group Co., Ltd, Hangzhou, 310020, China, E-mail:huafenglou@outlook.com
Project Management
Received September 12, 2025; revised October 30, 2025; accepted November 4, 2025
Available online April 8, 2026
Abstract: Municipal construction projects play an important role in improving public well-being and promoting economic and social development. Comprehensive project management involves the coordinated integration of key elements such as schedule, cost, quality, and safety. However, current municipal project management often adopts a single-objective optimization approach, overlooking the complexity of multi-objective interactions. To this end, this paper innovatively combines the Ant Colony Optimization (ACO) algorithm, Fuzzy Logic (FL), and Immune Genetic Algorithm (IGA), and proposes a hybrid algorithm for solving multi-objective models of municipal construction projects. Through a structured and collaborative algorithm fusion strategy, it systematically addresses the fuzziness, complexity, and local optimality problems in the multi-objective management of municipal engineering, providing a novel and efficient solution for achieving the global optimal management of the project. Results show that the hybrid algorithm achieves an average accuracy of 98.7%, a data query rate of 99.5%, a spatial complexity of 21.3%, and a computational speed of 17.6 bps. Its overall performance surpasses that of similar algorithms. Meanwhile, the Pareto solutions cover the entire objective space, demonstrating excellent computational efficiency and global optimization ability. Therefore, the hybrid algorithm exhibits outstanding optimization performance and practical applicability, providing a reference for multi-objective optimization (MOO) management in municipal construction projects.
Keywords: Municipal construction, ant colony optimization algorithm, multi-objective management, project optimization, immune genetic algorithm.
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Citation: Lou, H. (2026). Optimization of Municipal Construction Project Management Using Multi-Objective IGA. Journal of Engineering, Project, and Production Management, 16(3), 2025-202.
