Parallelization Strategies for Ant Colony Optimization
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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In this paper, the insufficiencies of current optimization algorithms in solving large-scale transmission network expansion planning (TNEP) problems are discussed. Then, the mathematical model of TNEP is formulated, and the schema of its solution is studied detailedly. After the main disadvantages of traditional ant colony algorithm (ACA) are discussed, a schema recording parallel ant colony algorithm (SRPACA) is proposed. It can partition the solution space through schema recording, and can identify, record and jump away from the local optimal solution. The simulation results of two practical systems show that this algorithm has high computation efficiency and good local & global convergence.