An efficient and global interactive optimization methodology for path planning with multiple routing constraints. (February 2022)

• Record Type: Journal Article
• Authors: Xie, Guo; Du, Xulong; Li, Siyu; Yang, Jing; Hei, Xinhong; Wen, Tao
• Is Part Of: ISA transactions. Volume 121(2022)
• Page Start: 206
• Page End: 216
• Publication Date: 2022-02
• Subjects: Path planning -- Multiple routing constraints -- Global optimization methodology -- Specified vertexes -- Specified paths; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2021.03.041
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: Path planning problem is attracting wide attention in autonomous system and process industry system. The existed research mainly focuses on finding the shortest path from the source vertex to the termination vertex under loose constraints of vertex and edge. However, in realistic, the constraints such as specified vertexes, specified paths, forbidden paths and forbidden vertexes have to be considered, which makes the existing algorithms inefficient even infeasible. Aiming at solving the problems of complex path planning with multiple routing constraints, this paper organizes transforms the constraints into appropriate mathematical analytic expressions. Then, in order to overcome the defects of existing coding and optimization algorithms, an adaptive strategy for the vertex priority is proposed in coding, and an efficient and global optimization methodology based on swarm intelligence algorithms is put forward, which can make full use of the high efficiency of the local optimization algorithm and the high search ability of the global optimization algorithm. Moreover, the optimal convergence condition of the methodology is proved theoretically. Finally, two experiments are inducted, and the results demonstrated its efficiency and superiority. Highlights: The constraints are transformed into mathematical analytic expressions. An adaptive strategy for the vertex priority in coding is proposed. A methodology based on swarm intelligence algorithms is proposed. The convergence condition of the methodology is proved theoretically. Results confirm the effectiveness and superiority of the proposed methodology.