A Novel Swarm Optimisation Algorithm Based on a Mixed-Distribution Model

Zhang, Xiaoming; Feng, Tinghao; Niu, Qingsong; Deng, Xiaorong

doi:10.3390/app8040632

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…For example, the distribution of the offspring of a BOA based on normal distribution is as follows: where 1. N (µ, δ) refers to a normal distribution with a probability density function f (X ) At present, research has been conducted on the preliminary design and implementation of the BOA [7], initial improvement of the algorithm, preliminary theoretical analysis of the algorithm [22], preliminary application experiments, improvement of the population distribution evolution model [23], intersection of a chaotic idea [24], typical dynamic optimization problem-solving, and simple multi-objective optimization problem-solving. This lays a preliminary foundation for application of the BOA to swarm robots.…”

Section: B Basic Principle Of the Boamentioning

confidence: 99%

A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments

Zhang

Mohsin

2020

IEEE Access

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This paper studies the target searching problem using swarms of unmanned aerial vehicles (UAVs) in unknown environments which information is unknown to the UAVs, other than features they detect through their sensors. Effective decision and control methods are required for UAVs that consider their limitations and characteristics when confronted with target searching problems. A cooperative target searching method is proposed for swarm UAVs based on an improved bean optimization algorithm (BOA) called Robot Bean Optimization Algorithm (RBOA). Compared with conventional BOAs used for optimal computation, RBOA has two main modifications for the cooperative control of swarm robots: 1) it accounts for the free motion space of individual UAVs using a Thiessen polygon; and 2) it adds a free space search mechanism to improve the efficiency of target searching. Based on the above improvements, and by integrating a multi-phase search mechanism and scheduling control strategy, a swarm UAV collaborative search simulation platform is built for experimental purposes. The results obtained from search simulations show that the RBOA can outperform adaptive robotic particle swarm optimization (A-RPSO) in target searches in complex and unknown environments, especially with fewer evolutionary generations and smaller numbers of robots. The RBOA, which is inspired by plant population evolutionary patterns, has fast and effective search capabilities, distributed collaborative interaction, and emergent swarm intelligence. It provides new ideas and support for research into the control of swarm UAVs and swarm robots.

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Section: B Basic Principle Of the Boamentioning

confidence: 99%

A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments

Zhang

Mohsin

2020

IEEE Access

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“…Theoretically, the optimized coefficient should minimize the value of the LSF along the search direction. However, it requires the exact line search to result in considerable computational effort [38][39][40]. For most optimization algorithms, the convergence rate does not depend on the exact search process.…”

Section: Adaptive Finite Step Length Algorithmmentioning

confidence: 99%

A Novel Algorithm for Structural Reliability Analysis Based on Finite Step Length and Armijo Line Search

Huang

2019

Applied Sciences

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This paper presents a novel algorithm for structural reliability analysis based on the finite step length and Armijo line search to remove the drawbacks of the Hasofer–Lind and Rakwitz–Fiessler (HL-RF) algorithm that may be subjected to non-convergence in the first-order reliability method (FORM). Initially, the sensitivity factor with finite step length is introduced for preventing the iterative process of the algorithm from entering a periodic loop. Subsequently, an optimization method based on the sufficient descent condition with the Armijo line search technique is proposed. With that, the initial step length and adjusting coefficient are optimized to enhance the applicability of the algorithm emphatically for highly nonlinear functions. A comparison analysis is carried out between the proposed algorithm and existing FORM-based algorithms to validate the robustness and efficiency of the proposed algorithm. The results of this demonstrate that the proposed algorithm is superior to the HL-RF algorithm in terms of robustness and surpass the other existing FORM-based algorithms in connection to efficiency.

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“…At present, the research of BOA has completed the following contents, including the preliminary design and implementation of BOA [25], the preliminary convergence analysis of BOA [26], introducing the negative binomial distribution into BOA [27], chaotic BOA [28], and so on.…”

Section: Introduction To the Boa And Rboamentioning

confidence: 99%

A Novel Target Searching Algorithm for Swarm UAVs Inspired From Spatial Distribution Patterns of Plant Population

Zhang¹,

Hu²,

Li³

2020

IJCIS

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Like some social animal groups, the evolution of plant populations in nature also contains swarm intelligence. Aiming at the problem of swarm Unmanned Aerial Vehicles (UAVs) target searching in complex and unknown environments, this paper explores search models suitable for swarm UAVs by investigating the spatial distribution patterns of plant population and proposes a novel robot bean optimization algorithm (RBOA) based on Cauchy distribution and normal distribution (CRBOA). It has been demonstrated by comparative experiments with RBOA and adaptive robotic particle swarm optimization (A-RPSO) that the CRBOA has excellent stability, striking a good balance between exploration and exploitation.

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A Novel Swarm Optimisation Algorithm Based on a Mixed-Distribution Model

Cited by 9 publications

References 29 publications

A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments

A Bean Optimization-Based Cooperation Method for Target Searching by Swarm UAVs in Unknown Environments

A Novel Algorithm for Structural Reliability Analysis Based on Finite Step Length and Armijo Line Search

A Novel Target Searching Algorithm for Swarm UAVs Inspired From Spatial Distribution Patterns of Plant Population

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