A hybrid optimization approach based on clustering and chaotic sequences

Gálvez, Jorge; Cuevas, Erik; Becerra, Héctor M.; Ávalos, Omar

doi:10.1007/s13042-019-00979-6

Cited by 25 publications

(4 citation statements)

References 70 publications

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“…For instance, in Ref. [ 33 ], chaotic sequences are applied to dynamically improve population size to avoid immature convergence; in Ref. [ 34 ], chaotic sequences are used in the generation of the initial population and the performance of the mutation operators.…”

Section: Details Of Optimization Techniquesmentioning

confidence: 99%

A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV

Liu

Shu

Liang

et al. 2021

Sensors

180

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The unmanned aerial vehicle (UAV) route planning problem mainly centralizes on the process of calculating the best route between the departure point and target point as well as avoiding obstructions on route to avoid collisions within a given flight area. A highly efficient route planning approach is required for this complex high dimensional optimization problem. However, many algorithms are infeasible or have low efficiency, particularly in the complex three-dimensional (3d) flight environment. In this paper, a modified sparrow search algorithm named CASSA has been presented to deal with this problem. Firstly, the 3d task space model and the UAV route planning cost functions are established, and the problem of route planning is transformed into a multi-dimensional function optimization problem. Secondly, the chaotic strategy is introduced to enhance the diversity of the population of the algorithm, and an adaptive inertia weight is used to balance the convergence rate and exploration capabilities of the algorithm. Finally, the Cauchy–Gaussian mutation strategy is adopted to enhance the capability of the algorithm to get rid of stagnation. The results of simulation demonstrate that the routes generated by CASSA are preferable to the sparrow search algorithm (SSA), particle swarm optimization (PSO), artificial bee colony (ABC), and whale optimization algorithm (WOA) under the identical environment, which means that CASSA is more efficient for solving UAV route planning problem when taking all kinds of constraints into consideration.

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Section: Details Of Optimization Techniquesmentioning

confidence: 99%

A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV

Liu

Shu

Liang

et al. 2021

Sensors

180

View full text Add to dashboard Cite

show abstract

“…If certain systems evolve from two nearest points, after a sufficient amount of time, they would be infinitely far apart. The chaotic attractor's time patterns are entirely irregular, with no recurrence in any monitoring period of the final length [20]. Although the state is generated by a deterministic equation, there is arbitrariness in the temporal domain and long-term uncertainty in the state.…”

Section: Objective Function and Coamentioning

confidence: 99%

The Numerical Algorithms and Optimization Approach Used in Extracting the Parameters of the Single-Diode and Double-Diode Photovoltaic (PV) Models

Prabu

Swaminathan

Sahoo

et al. 2022

International Journal of Photoenergy

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The current-voltage association of the single-diode photovoltaic (PV) cell comparable circuit system was characterized by its nonlinear implicit logical equation that would be hard to be resolved numerically. Because of the difficulty, various strategies for explaining this equation by using numerical approaches have been developed. The double-diode model is used to depict the PV cell in this research. This design is more accurate at the low irradiance levels, allowing for an extra accurate estimate performance of the PV system. The number of input variables is decreased to four to save time, and the values of R p and R s are calculated using an effective iterative technique. This research analyzes and compares three commonly used strategies for explaining the current-voltage equation parameter of a single-diode solar PV model. The chaotic optimization approach (COA) is used to evaluate the single-diode and double-diode solar cell characteristics. The suggested method relies on experimentally established current-voltage (I-V) characteristics. The suggested approach uses the curves of I-V characteristics obtained in the research laboratory for several standards of the solar temperature and the radiation and demonstrates its applicability in terms of efficacy, accuracy, and the simplicity of execution in an extensive range of real-world situations. As a conclusion, COA-based restriction approximation is beneficial to photovoltaic power generator manufacturers that want a timely and efficient PV cell/module model. It demonstrates that no single approach performs the best among all parameters and the method selection is always a trade-off depending on the user’s focus.

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“…A multiobjective integer programming model of UAV flight path was proposed by establishing a mathematical model through three-dimensional grid cells. The author of [9] proposed an algorithm based on the clustering idea, which divides the region of waypoints of different individuals through clustering and obtains the approximate optimal waypoint of UAV so as to guide the generation of offspring. In [10,11], the authors studied the characteristics of the evolutionary algorithm (EA), analyzed the main problems in evolutionary algorithm path planning, and established an evaluation system for a single path point.…”

Section: Introductionmentioning

confidence: 99%

UAV Path Planning Based on Multi-Stage Constraint Optimization

Shen

Zhu

Kang

et al. 2021

Drones

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Evolutionary Algorithms (EAs) based Unmanned Aerial Vehicle (UAV) path planners have been extensively studied for their effectiveness and high concurrency. However, when there are many obstacles, the path can easily violate constraints during the evolutionary process. Even if a single waypoint causes a few constraint violations, the algorithm will discard these solutions. In this paper, path planning is constructed as a multi-objective optimization problem with constraints in a three-dimensional terrain scenario. To solve this problem in an effective way, this paper proposes an evolutionary algorithm based on multi-level constraint processing (ANSGA-III-PPS) to plan the shortest collision-free flight path of a gliding UAV. The proposed algorithm uses an adaptive constraint processing mechanism to improve different path constraints in a three-dimensional environment and uses an improved adaptive non-dominated sorting genetic algorithm (third edition—ANSGA-III) to enhance the algorithm’s path planning ability in a complex environment. The experimental results show that compared with the other four algorithms, ANSGA-III-PPS achieves the best solution performance. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of UAV path planning.

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A hybrid optimization approach based on clustering and chaotic sequences

Cited by 25 publications

References 70 publications

A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV

A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV

The Numerical Algorithms and Optimization Approach Used in Extracting the Parameters of the Single-Diode and Double-Diode Photovoltaic (PV) Models

UAV Path Planning Based on Multi-Stage Constraint Optimization

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