Abstract
In this paper, a mathematical model for multiconstrained routing optimization problem is established. The multi-objective optimization problem is transformed into a single-objective optimization problem by adding a penalty function. Then the artificial bee colony algorithm (ABC) is used for route search. Because the ABC algorithm is easy to fall into the local optimal deficiencies, the dynamic fireworks algorithm (dynFWA) is introduced for local search, which can ensure fast global search and fast guarantee. In the process of searching for the optimal solution, the success rate is improved by about 1.05% compared with the PSO_ACO algorithm optimized by the ant colony algorithm, which is 6.18% higher than the standard PSO algorithm and the standard ABC algorithm. The minimum average cost of the search is about 0.53% higher than the PSO_ACO algorithm, which is about 1.87% higher than the other two algorithms. The simulation results show that the algorithm can effectively solve the multiconstrained routing problem under large-scale networks.
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