Swarm Intelligence in Engineering
Baozhen Yao, Rui Mu, Bin Yu · Mathematical Problems in Engineering · 2013
Swarm intelligence (SI) is an artificial intelligence techniquebased on the study of behavior of simple individuals (e.g., ant colonies, bird flocking, animal herding, and honey bees), which has attracted much attention of researchers and has also been applied successfully to solve optimization problems in engineering.However, for large and complex problems, SI algorithms consume often much computation time due to stochastic feature of the search approaches.Therefore, there is a potential requirement to develop efficient algorithm to find solutions under the limited resources, time, and money in real-world applications.Within this context, this special issue servers as a forum to highlight the most significant recent developments on the topics of SI and to apply SI algorithms in real-life scenario.The works in this issue contain new insights and findings in this field.A broad range of topics has been discussed, especially in the following areas, benchmarking and evaluation of new SI algorithms, convergence proof for SI algorithms, comparative theoretical and empirical studies on SI algorithms, and SI algorithms for real-world application.Some works focus on the application of genetic algorithm in different area, for example, G. Ning et al. 's "Economic analysis on value chain of taxi fleet with battery-swapping mode using multiobjective genetic algorithm" presents an economic analysis model on value chain of taxi fleet with battery-swapping mode in a pilot city.A multiobjective genetic algorithm is used to solve the problem.The real data collected from the pilot city proves that the multiobjective genetic algorithm is tested as an effective method to solve this problem.