دورية أكاديمية
أعرض في EDS

Enhanced Teaching–Learning-Based Optimization Algorithm for the Mobile Robot Path Planning Problem

التفاصيل البيبلوغرافية
العنوان: Enhanced Teaching–Learning-Based Optimization Algorithm for the Mobile Robot Path Planning Problem
المؤلفون: Shichang Lu, Danyang Liu, Dan Li, Xulun Shao
المصدر: Applied Sciences, Vol 13, Iss 4, p 2291 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: optimization, metaheuristic, path planning, divide-and-conquer, teaching–learning based optimization algorithm, differential evolution, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: This research proposes an enhanced teaching–learning based optimization (ETLBO) algorithm to realize an efficient path planning for a mobile robot. Four strategies are introduced to accelerate the teaching–learning based optimization (TLBO) algorithm and optimize the final path. Firstly, a divide-and-conquer design, coupled with the Dijkstra method, is developed to realize the problem transformation so as to pave the way for algorithm deployment. Secondly, the interpolation method is utilized to smooth the traveling route as well as to reduce the problem dimensionality. Thirdly, an opposition-based learning strategy is embedded into the algorithm initialization to create initial solutions with high qualities. Finally, a novel, individual update method is established by hybridizing the TLBO algorithm with differential evolution (DE). Simulations on benchmark functions and MRPP problems are conducted, and the proposed ELTBO is compared with some state-of-the-art algorithms. The results show that, in most cases, the ELTBO algorithm performs better than other algorithms in both optimality and efficiency.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/13/4/2291; https://doaj.org/toc/2076-3417
DOI: 10.3390/app13042291
URL الوصول: https://doaj.org/article/7d39f665f7b546fb9e33239a3171d408
رقم الأكسشن: edsdoj.7d39f665f7b546fb9e33239a3171d408
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app13042291