摘要
针对医疗废弃物回收量的不确定性、多周期性,以及部分有毒有害废弃物处理不当不仅污染环境,还会危及操作人员健康等问题,以最小经济成本、最小环境影响、最大社会效益为目标,构建了不确定条件下医疗废弃物多目标多周期可持续性回收网络模型。为了减少不确定参数的影响,采用模糊机会约束方法,将模型中的模糊约束转换为清晰的对应式。以上海市某医疗废弃物回收企业为例,采用遗传算法(GA)对模型进行求解。算例结果表明,多目标优化总体优于单目标优化,且多周期回收网络规划比单周期规划更加灵活。
With the consideration of the uncertainty of medical waste recovery,and in view of the fact that multi-periodicity and improper treatment of some toxic and hazardous wastes not only pollute the environment,but also endanger the health of operators,a multi-objective multi-period sustainable recycling network model for medical waste under uncertain conditions was established aiming at minimizing economic cost,and environmental impact and maximizing social benefit.In order to reduce the influence of uncertain parameters,the fuzzy opportunity constraint method was adopted to convert the fuzzy constraints in the model into clear corresponding expressions.Taking a medical waste recycling enterprise in Shanghai as an example,a genetic algorithm(GA)was used to solve the model.The example results show that the multi-objective optimization is better than the single-objective optimization in general,and the multi-period recovery network planning is more flexible than the singleperiod planning.
作者
霍晴晴
郭健全
HUO Qingqing;GUO Jianquan(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China;Sino-German College,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《上海理工大学学报》
CAS
CSCD
北大核心
2020年第5期479-487,共9页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(71071093,71471110)
上海市科委创新项目(16DZ1201402,16040501500)
陕西省社会科学基金资助项目(2015D060)。
关键词
医疗废弃物
不确定性
多目标
多周期
可持续回收网络
模糊
遗传算法
medical waste
uncertainty
multi-objective
multi-period
sustainable recycling network
fuzzy
genetic algorithm