摘要
畜禽养殖废弃物的合理处置,是农村生态环境治理与污染防治的关键点。为解决畜禽养殖废弃物的运输路径问题,提出一种改进鲸鱼优化算法的车辆路径优化方法。首先,在车辆路径优化问题的基础上,建立以总路程最小化为目标的畜禽养殖废弃物运输路径优化模型;其次,结合离散型问题特征和鲸鱼优化算法的寻优思想,提出改进鲸鱼优化算法。引入升序排列(ranked order value,ROV)转换机制使该算法能够求解离散问题,对每次迭代结果进行聚类分析,将优秀个体所在类依次进行基于位置的交叉(position-based crossover,PBX)操作和逆序变异操作,同时保证了种群的多样性和算法的求解效率;最后,对9个Solomon算例和1个实例进行仿真实验,并与改进粒子群优化算法、改进灰狼优化算法和改进蚁群算法进行对比。结果表明,改进鲸鱼优化算法在9个案例中均优于其他算法,在最复杂的RC103案例中,求解结果相较于其他算法至少提高14.64%,体现了改进鲸鱼优化算法有更高的求解精度和稳定性;对于畜禽废弃物运输实例仿真实验,改进鲸鱼优化算法比其他算法分别提高4.9%、6.5%和43.7%,证明本文算法能够有效地解决畜禽养殖废弃物运输路径优化问题。
Rational disposal of livestock and poultry breeding waste is the key point of rural ecological environment control and pollution prevention.In order to solve the transportation path problem of livestock and poultry waste,a vehicle path optimization method based on improved whale optimization algorithm was proposed.Firstly,based on the vehicle routing optimization problem,an optimization model of livestock and poultry waste transportation path was established with the goal of minimizing the total distance.Secondly,an improved whale optimization algorithm was proposed combining the characteristics of discrete problem and the thought of whale optimization algorithm.The ranked order value(ROV)mechanism was introduced to enable the algorithm to solve discrete problems,perform cluster analysis on the results of each iteration,and perform position-based crossover(PBX)operation and reverse mutation operation on the classes of excellent individuals in turn,ensuring the diversity of population and solving efficiency of the algorithm.Finally,nine Solomon examples and one Solomon example were simulated and compared with improved particle swarm optimization,improved gray wolf optimization and improved ant colony optimization.The results show that the improved whale optimization algorithm is superior to other algorithms in all 9 cases.In the most complex RC103 case,the solution result is increased at least 14.64%compared with other algorithms,indicating that the improved whale optimization algorithm has higher solution accuracy and stability.For the simulation experiment of livestock and poultry waste transportation,the improved whale optimization algorithm is 4.9%,6.5%and 43.7%higher than other algorithms,respectively,proving that the proposed algorithm can effectively solve the optimization problem of livestock and poultry waste transportation path.
作者
路雪刚
张雪花
张梦桃
LU Xue-gang;ZHANG Xue-hua;ZHANG Meng-tao(School of Economics and Management,Tiangong University,Tianjin 300387,China;School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing 100876,China)
出处
《科学技术与工程》
北大核心
2022年第25期11120-11129,共10页
Science Technology and Engineering
基金
国家社会科学基金(18BJY079)。
关键词
养殖废弃物
运输路径
鲸鱼优化算法
反向学习策略
基于位置的交叉
farming waste
transport path
whale optimization algorithm
opposition-based learning strategies
position-based crossover
作者简介
第一作者:路雪刚(1992-),男,汉族,山东滨州人,硕士研究生。研究方向:智能优化方法。E-mail:757263435@qq.com;通信作者:张雪花(1967-),女,汉族,河北秦皇岛人,博士,教授,博士研究生导师。研究方向:系统科学与资源环境管理。E-mail:xuehua671231@163.com。
