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作 者:刘蕾 Lei Liu(School of Business,Jiangnan University,Wuxi Jiangsu)
机构地区:[1]江南大学商学院,江苏无锡
出 处:《运筹与模糊学》2024年第3期406-416,共11页Operations Research and Fuzziology
摘 要:日益复杂的城市交通状况和持续增加的医疗废弃物数量,导致回收工作面临成本上升和疾病传播的问题。本研究考虑了交通拥堵对医疗废弃物回收工作的不利影响,提出了一个以最小化运输成本为目标的数学模型,并采用改进的遗传算法求解。数值实验结果表明,相较于传统遗传算法,改进的遗传算法通过增加遗传操作多样性、降低过早收敛的风险,显著提高了全局搜索性能。研究所得的运输方案可为城市医疗废弃物回收工作提供优化建议。The increasingly complex urban traffic conditions and the increasing amount of medical waste lead to the problems of rising costs and disease transmission in recycling work.Considering the adverse impact of traffic congestion on medical waste recycling work,this paper proposes a ma-thematical model with the goal of minimizing transportation cost,and adopts an improved genetic algorithm to solve it.The numerical experimental results show that compared with the traditional genetic algorithm,the improved genetic algorithm significantly improves the global search per-formance by increasing the diversity of genetic operations and reducing the risk of premature convergence.The transportation scheme obtained in this study can provide optimization sugges-tions for the recycling work of medical waste in cities.
关 键 词:交通拥堵 医疗废弃物 回收网络 路径规划 改进的遗传算法
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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