关键词：
鸟群算法;自适应随机惯性权重;农产品冷链物流配送;路径优化
摘 要：
鸟群算法(BSA)在求解高维复杂的优化问题时,很容易陷入局部极值,尤其在鸟群觅食过程中总会出现"早熟"现象。针对原鸟群算法的不足,提出一种改进的鸟群优化算法(WBSA)。通过仿真试验,结果表明,提出的算法具有较好的收敛速度和寻优精度。最后,通过对农产品冷链物流配送优化路径模型的简化,构建求解农产品冷链物流配送路径优化问题的WBSA优化算法,利用数值实例表明WBSA算法对此类问题具有可行性和有效性。
译 名：
Optimization Problem of Cold Chain Logistics Distribution Path of Agricultural Products Based on Improved Algorithm of Bird Swarm Optimization
作 者：
WANG Jin-cheng;GAO Yue-lin;School of Mathematics and Statistics,Ningxia University;Research Institute of Information and System Computation Science,North Minzu University;
单 位：
WANG Jin-cheng%GAO Yue-lin%School of Mathematics and Statistics,Ningxia University%Research Institute of Information and System Computation Science,North Minzu University
关键词：
Bird swarm algorithm;;Adaptive random inertial weight;;Cold chain logistics distribution of agricultural products;;Path optimization
摘 要：
Birds algorithm( BSA) is easy to fall into local extremum in solving the problem of optimization of high-dimensional complex,especially it always appeared a"premature"phenomenon in the process of the flock foraging. Aiming at the shortcomings of the original algorithm of the flock,and an improved optimization algorithm( WBSA) birds was put forward. Based on the simulation experiment,results showed that the presented algorithm had better convergence speed and searching precision. In the end,through simplifying agricultural products cold chain logistics distribution optimization path model,WBSA optimization algorithm of agricultural products cold chain logistics distribution route optimization problem was built. The numerical examples showed that WBSA algorithm had the feasibility and validity of such problem.
