同济大学学报（自然科学版）2024，Vol.52Issue(1)：27-34,8.DOI:10.11908/j.issn.0253-374x.23388
基于改进遗传算法的家电回收车辆路径规划方法
Path Planning Method for Household Appliance Recycling Vehicle Based on Improved Genetic Algorithm
摘要
Abstract
In order to improve the recycling efficiency and reduce the cost of recycling disused products,a path optimization method for recycling vehicles based on a modified genetic algorithm(GA)was proposed.Firstly,the path planning problem for the recycling vehicle was modeled as a variant of the traveling salesman problem(TSP),aiming at minimizing transportation costs,which,however,is an NP-hard problem.Then,an improved genetic algorithm based on the Gaussian matrix mutation(GMM)operator was put forward.The algorithm leveraged the site order distribution characteristics hidden behind the original station data information to establish a Gaussian probability matrix.The Gaussian probability matrix was then applied to individual gene mutations combined with the roulette selection method,so as to guide the population to evolve towards high fitness while maintaining the genetic diversity.Finally,comprehensive simulations were carried out using the actual data collected from recycling sites in Shanghai to validate the proposed algorithm,and compared with other algorithms.The simulation results show that the proposed algorithm can increase the average convergence speed by 50%～60%and reduce the time consumption by 48%compared with the traditional genetic algorithm,under the precision gap within 1%.关键词
家电回收/旅行商问题(TSP)/遗传算法(GA)/高斯矩阵变异(GMM)算子Key words
household appliance recycling/traveling salesman problem(TSP)/genetic algorithm(GA)/Gaussian matrix mutation(GMM)operator分类
信息技术与安全科学引用本文复制引用
黄新林,张隆飛,唐小伟..基于改进遗传算法的家电回收车辆路径规划方法[J].同济大学学报（自然科学版）,2024,52(1):27-34,8.基金项目
国家重点研发计划(2022YFB3305801) （2022YFB3305801）
