Path-Planning for Mobile Robots Using a Novel Variable-Length Differential Evolution Variant

Rodríguez-Molina, Alejandro; Solís-Romero, José; Villarreal-Cervantes, Miguel Gabriel; Serrano-Pérez, Omar; Flores-Caballero, Geovanni

doi:10.3390/math9040357

Cited by 10 publications

(5 citation statements)

References 65 publications

(69 reference statements)

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“…The feasible region of many problems is uncertain in real life. Many scholars [23][24][25][26][27][28][29] have improved the NSGA-III-VLC according to the characteristics of the problem. In the formulation of the equipment usage plan considering rotation, because the quantity of rotation will affect the rotation cost and risk, the length of the chromosome also affects the decision-making.…”

Section: Principle Of I-nsga-iii-vlc Methodsmentioning

confidence: 99%

Modeling and I-NSGA-III-VLC Solution of Aircraft Equipment Rotation and Echelon Usage under Uncertainty

Miao¹,

Zhang²,

Qin³

et al. 2022

Applied Sciences

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Optimizing the aircraft equipment usage scheme of different units according to their task intensity has great significance in improving aircraft reliability and health management. This paper studied the modeling and solving methods of the rotation and echelon usage problems of aircraft equipment measured by dual-life indexes, one of which cannot be controlled. In order to maximize the waste rate of the rotation quantity, echelon uniformity index, life matching index and life utilization index, a decision-making model of the equipment rotation and echelon usage problem under uncertainty was constructed, and an improved NSGA-III with a variable length chromosome was proposed. An improved segmented coding method and operators were proposed, and the repeated individual control mechanism was used to improve the population diversity. When the scale of the problem was large, this method could search a wider range in a short time and obtain more feasible solutions, which verified the feasibility of this method.

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Section: Principle Of I-nsga-iii-vlc Methodsmentioning

confidence: 99%

Modeling and I-NSGA-III-VLC Solution of Aircraft Equipment Rotation and Echelon Usage under Uncertainty

Miao¹,

Zhang²,

Qin³

et al. 2022

Applied Sciences

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“…Like the genetic algorithm, the differential evolution (DE) [29,30] algorithm is an optimization algorithm based on the modern intelligence theory, which guides the direction of the optimization search through the group intelligence generated by cooperation and competition among individuals within a population. It continuously evolves to retain suitable individuals and eliminate inferior ones, guiding the search for the optimal solution.…”

Section: Differential Evolution (De)mentioning

confidence: 99%

A Cooperative Game Hybrid Optimization Algorithm Applied to UAV Inspection Path Planning in Urban Pipe Corridors

Wang,

Zhang,

Gao

et al. 2023

Mathematics

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This paper proposes an improved algorithm applied to path planning for the inspection of unmanned aerial vehicles (UAVs) in urban pipe corridors, which introduces a collaborative game between spherical vector particle swarm optimization (SPSO) and differential evolution (DE) algorithms. Firstly, a high-precision 3D grid map model of urban pipe corridors is constructed based on the actual urban situation. Secondly, the cost function is formulated, and the constraints for ensuring the safe and smooth inspection of UAVs are proposed to transform path planning into an optimization problem. Finally, a hybrid algorithm of SPSO and DE algorithms based on the Nash bargaining theory is proposed by introducing a cooperative game model for optimizing the cost function to plan the optimal path of UAV inspection in complex urban pipe corridors. To evaluate the performance of the proposed algorithm (GSPSODE), the SPSO, DE, genetic algorithm (GA), and ant colony optimization (ACO) are compared with GSPSODE, and the results show that GSPSODE is superior to other methods in UAV inspection path planning. However, the selection of algorithm parameters, the difference in the experimental environment, and the randomness of experimental results may affect the accuracy of experimental results. In addition, a high-precision urban pipe corridors scenario is constructed based on the RflySim platform to dynamically simulate the optimal path planning of UAV inspection in real urban pipe corridors.

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“…Additionally, as per concern, in the application area, the authors utilized BA for the antenna optimization problem in [55], moreover, pan evaporation was estimated by using BA [56]. Beside this, in [57], the authors applied a new variant of DE for path-planning of mobile robots.…”

Section: Previous Workmentioning

confidence: 99%

Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

et al. 2021

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To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. These algorithms can affect convergence to identify a robust optimum solution. To investigate the effectiveness of diversity, many scholars have a focus on the reliability and quality of meta-heuristic algorithms for enhancement. To initialize the population in the search space, this dissertation proposes three new low discrepancy sequences for population initialization instead of uniform distribution called the WELL sequence, Knuth sequence, and Torus sequence. This paper also introduces a detailed survey of the different initialization methods of PSO and DE based on quasi-random sequence families such as the Sobol sequence, Halton sequence, and uniform random distribution. For well-known benchmark test problems and learning of artificial neural network, the proposed methods for PSO (TO-PSO, KN-PSO, and WE-PSO), BA (BA-TO, BA-WE, and BA-KN), and DE (DE-TO, DE-WE, and DE-KN) have been evaluated. The synthesis of our strategies demonstrates promising success over uniform random numbers using low discrepancy sequences. The experimental findings indicate that the initialization based on low discrepancy sequences is exceptionally stronger than the uniform random number. Furthermore, our work outlines the profound effects on convergence and heterogeneity of the proposed methodology. It is expected that a comparative simulation survey of the low discrepancy sequence would be beneficial for the investigator to analyze the meta-heuristic algorithms in detail.

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Path-Planning for Mobile Robots Using a Novel Variable-Length Differential Evolution Variant

Cited by 10 publications

References 65 publications

Modeling and I-NSGA-III-VLC Solution of Aircraft Equipment Rotation and Echelon Usage under Uncertainty

Modeling and I-NSGA-III-VLC Solution of Aircraft Equipment Rotation and Echelon Usage under Uncertainty

A Cooperative Game Hybrid Optimization Algorithm Applied to UAV Inspection Path Planning in Urban Pipe Corridors

Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

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