Minimum dose path planning for facility inspection based on the discrete Rao-combined ABC algorithm in radioactive environments with obstacles

作     者：Kwon Ryong Hong Su Il O Ryon Hui Kim Tae Song Kim Jang Su Kim Kwon Ryong Hong;Su Il O;Ryon Hui Kim;Tae Song Kim;Jang Su Kim

作者机构：Faculty of Energy ScienceKim Il Sung UniversityPyongyangDemocratic People’s Republic of Korea High-Tech Research&Development CentreInstitute of Information TechnologyKim Il Sung UniversityPyongyangDemocratic People’s Republic of Korea 

出 版 物：《Nuclear Science and Techniques》 (核技术（英文）)

年 卷 期：2023年第34卷第4期

页      面：26-40页

核心收录：

学科分类：082704[工学-辐射防护及环境保护] 08[工学] 0827[工学-核科学与技术] 0702[理学-物理学] 

主　　题：Minimum dose Path planning Nuclear facility inspection ABC algorithm Rao algorithms Swap sequence K-opt operation 

摘      要：Workers who conduct regular facility inspections in radioactive environments will inevitably be affected by radiation.Therefore,it is important to optimize the inspection path to ensure that workers are exposed to the least amount of radiation.This study proposes a discrete Rao-combined artificial bee colony(ABC)algorithm for planning inspection paths with minimum exposure doses in radioactive environments with obstacles.In this algorithm,retaining the framework of the traditional ABC algorithm,we applied the directional solution update rules of Rao algorithms at the employed bee stage and onlooker bee stage to increase the exploitation ability of the algorithm and implement discretion using the swap operator and swap sequence.To increase the randomness of solution generation,the chaos algorithm was used at the initialization stage.The K-opt operation technique was introduced at the scout bee stage to increase the exploration ability of the algorithm.For path planning in an environment with complex structural obstacles,an obstacle detour technique using a recursive algorithm was applied.To evaluate the performance of the proposed algorithm,we performed experimental simulations in three hypothetical environments and compared the results with those of improved particle swarm optimization,chaos particle swarm optimization,improved ant colony optimization,and discrete Rao’s algorithms.The experimental results show the high performance of the proposed discrete Rao-combined ABC algorithm and its obstacle detour capability.