Zhang, Jiashan; Lin, Xiaoqun An improved artificial bee colony with self-adaptive strategies and application in the VRP. (Chinese. English summary) Zbl 1438.68315 Math. Pract. Theory 48, No. 23, 89-95 (2018). Summary: In order to overcome the shortcomings of low convergence rate and premature convergence in artificial bee colony algorithm (ABC), this paper proposes an improved artificial bee colony algorithm with self-adaptive strategies (IABCWSAS). First, self-adaptive strategies for updating food source are introduced to enhance the convergence rate and optimization precision. Second, in order to maintain the population diversity, an effective mutation is utilized when the particles go beyond the boundary. Third, correcting mechanism for inferior solutions is introduced to ensure the efficiency of iteration. The IABCWSAS is also applied to vehicle routing problems. Experiment results show the effectiveness of the improved algorithm. MSC: 68W50 Evolutionary algorithms, genetic algorithms (computational aspects) 90C27 Combinatorial optimization 90C59 Approximation methods and heuristics in mathematical programming Keywords:artificial bee colony algorithm; self-adaptive strategies; population diversity; vehicle routing problem PDFBibTeX XMLCite \textit{J. Zhang} and \textit{X. Lin}, Math. Pract. Theory 48, No. 23, 89--95 (2018; Zbl 1438.68315)