The Sustainable Allocation of Earth-Rock via Division and Cooperation Ant Colony Optimization Combined with the Firefly Algorithm
Open Access
Abstract
Optimized earth-rock allocation is key in the construction of large-scale navigation channel projects. This paper analyzes the characteristics of a large-scale navigation channel project and establishes an earth-rock allocation system in phases and categories without a transit field. Based on the physical characteristics of the earthwork and stonework used to design a differentiated transport strategy, a synergistic optimization model is built with economic and ecological benefits. As a solution, this paper proposes a sustainable earth-rock allocation optimization method that integrates the improved ant colony algorithm and firefly algorithm, and establishes a two-stage hybrid optimization framework. The application of the Pinglu Canal Project shows that ant colony optimization via division and cooperation combined with the firefly algorithm reduces the transportation cost by 0.128% compared with traditional ant colony optimization; improves the stability by 57.46% (standard deviation) and 59.09% (coefficient of variation) compared with ant colony optimization through division and cooperation; and effectively solves the problems of precocious convergence and local optimization of large-scale earth-rock allocation. It is used to successfully construct an earth-rock allocation model that takes into account the efficiency of the project and the protection of the ecological system in a dynamic environment.Keywords
This publication has 16 references indexed in Scilit:
- A Q-learning guided dual population genetic algorithm for distributed permutation flow shop scheduling problem with machine having fuzzy processing efficiencyExpert Systems with Applications, 2025
- Optimization of the earthwork excavation-filling balance and allocation for the upper reservoir of a pumped storage power stationJournal of Energy Storage, 2024
- Earthwork allocation optimisation based on cut-fill matching and transportation path planningInternational Journal of Automation and Control, 2024
- Reptile Search Algorithm: Theory, Variants, Applications, and Performance EvaluationArchives of Computational Methods in Engineering, 2023
- An improved heuristic mechanism ant colony optimization algorithm for solving path planningKnowledge-Based Systems, 2023
- Towards Developing a Robust Optimization Model of Earthwork Allocations in Roadway ProjectsIranian Journal of Science and Technology, Transactions of Civil Engineering, 2023
- A Modified Reptile Search Algorithm for Numerical Optimization ProblemsComputational Intelligence and Neuroscience, 2022
- Parameter adaptation-based ant colony optimization with dynamic hybrid mechanismEngineering Applications of Artificial Intelligence, 2022
- Path planning in uncertain environment by using firefly algorithmDefence Technology, 2018
- No free lunch theorems for optimizationIEEE Transactions on Evolutionary Computation, 1997