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作 者:张佑健 李莉[2] 吴瑕 狄宏林 ZHANG You-jian;LI Li;WU Xia;DI Hong-lin(Dongguan Open University,Dongguan,Guangdong 523000,China;Huizhou University,Huizhou,516007 Guangdong,China)
机构地区:[1]东莞开放大学,广东东莞523000 [2]惠州学院,广东惠州516007
出 处:《河北北方学院学报(自然科学版)》2023年第9期47-52,57,共7页Journal of Hebei North University:Natural Science Edition
基 金:广东省哲学社会科学规划2022年度常规项目“一核一带一区背景下基于产业集群的区域专业群构建研究”(GD22CJY08);2022年度广东远程开放教育科研基金重点项目“智能技术赋能社区教育个性化供给模式研究”(YJ2220);广东远程开放教育科研基金项目“创新视角下东莞产业集群演化升级路径研究”(YJ1604)。
摘 要:为优化电网企业项目管理,实现电网企业工程项目中TCTP的平衡,降低物流成本,在构建项目物流成本模型的基础上,通过ABC算法核算物流成本,了解物流工序中对应的物流费用情况,并进行物流工期计算。利用自适应权重和ANN算法改进ACO算法进行工程项目物流成本优化。结果显示,参数α、β、m、ρ会影响物流成本优化效果。固定m、ρ,分析α、β时,在α、β形成的组合7中,能够得到最小目标函数值,即该组合下α=0.2,β=0.2为最佳取值;根据这种分析方法可知蚂蚁数最佳取值为m=37,信息素挥发度ρ最佳取值为0.7。相较于ACO算法,改进ACO算法的收敛迭代更少,收敛迭代数为45,比ACO算法少27;工期-成本综合目标值更小。采用该方法有效降低了电网企业工程项目物流成本,实现了电网企业项目管理优化。To optimize project management of power grid enterprises,achieve balance of TCTP in power grid enterprise engineering projects,and reduce logistics costs,Based on the construction of the project logistics cost model,the logistics cost was calculated by ABC algorithm,the corresponding logistics cost in the logistics process was understood,and the logistics duration was calculated.ACO algorithm was improved by adaptive weight and ANN algorithm,which was used to optimize the logistics cost of engineering projects.The results showed that parametersα,β,m andρwould affect the logistics cost optimization effect.When m andρwere fixed andαandβwere analyzed,the minimum objective function value of 0.4434*105 could be obtained from the combination 7 formed byαandβ,that is,α=0.2,β=0.2 was the best value under the combination;According to this analysis method,the best value of ant number was m=37,and the best value of pheromone volatilityρwas 0.7.Compared with the ACO algorithm,the improved ACO algorithm had fewer convergence iterations,with 45 convergence iterations,27 less than the ACO algorithm;The comprehensive target value of duration and cost was smaller.Application of these methods can effectively reduce the logistics costs of power grid enterprise engineering projects and achieve optimization of project management in power grid enterprises.
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