An Improved Exhausted-Food-Sources-Identification Mechanism for the Artificial Bee Colony Algorithm

Ning, Jiaxu; Zhao, Haitong; Sun, Peng; Feng, Yundi; Tian-yu, Zhao

doi:10.1007/978-3-030-32216-8_62

Cited by 1 publication

(2 citation statements)

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“…In formula (7), x k is the current position of the particle, v k is the current velocity vector of the particle, pbest k is the optimal solution position currently found by the particle, gbest k is the optimal solution position currently found for the entire (3) Octree algorithm: the octree algorithm is also called a hierarchical tree structure, which is a tree-like data structure that describes a three-dimensional space [9]. e application of octree is mainly concentrated in the fields of computer graphics, computer vision, and image processing.…”

Section: Optimization Methods Of Artificial Bee Colony Algorithmmentioning

confidence: 99%

“…e algorithm model of artificial bee colony algorithm can be abstracted from the foraging model of natural bees. As an intelligent optimization algorithm, artificial bee colony algorithm can rely on the self-organization ability of bees to realize the positive and negative feedback mechanism of the algorithm [7]. In the following section, we present the algorithm model of artificial bee colony algorithm:…”

Section: Algorithm Model Of Artificial Bee Colonymentioning

confidence: 99%

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Shortest Path Selection Algorithm for Cold Chain Logistics Transportation Based on Improved Artificial Bee Colony

Liu

2021

Scientific Programming

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Aiming at the problems of low shortest path selection accuracy, longer response time, and poor selection effect in current cold chain logistics transportation methods, a cold chain logistics transportation shortest path selection algorithm based on improved artificial bee colony is proposed. The improved algorithm is used to initialize the food source, reevaluate the fitness value of the food source, generate a new food source, optimize the objective function and food source evaluation strategy, and get an improved artificial bee colony algorithm. Based on the improved artificial bee colony algorithm, the group adaptive mechanism of particle swarm algorithm is introduced to initialize the position and velocity of each particle randomly. Dynamic detection factor and octree algorithm are adopted to dynamically update the path of modeling environment information. According to the information sharing mechanism between individual particles, the group adaptive behavior control is performed. After the maximum number of cycles, the path planning is completed, the shortest path is output, and the shortest path selection of cold chain logistics transportation is realized. The experimental results show that the shortest path selection effect of the cold chain logistics transportation of the proposed algorithm is better, which can effectively improve the shortest path selection accuracy and reduce the shortest path selection time.

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Section: Optimization Methods Of Artificial Bee Colony Algorithmmentioning

confidence: 99%

Section: Algorithm Model Of Artificial Bee Colonymentioning

confidence: 99%