摘要
针对有毒重气泄漏事故具有发生的突然性、危害的严重性等特点。建立了以应急加权总时间、应急总成本最小化为目标的多需求点、多供应点、多物资类型的优化调度模型。为了增强模型的实用性,增加了对车辆载重及最优路径选择的考虑。利用改进了的Dijkstra算法,将其作为多目标粒子群优化算法的子算法对模型进行求解。针对多目标粒子优化算法易陷入局部最优解的缺点,对惯性权重的更新方式进行了设计,增强了算法的全局搜索能力,同时在对粒子进行选择操作时借鉴了自适应网格法的思想,丰富了粒子群的多样性。最后,通过一个仿真实验验证了所提模型及算法的有效性。
The toxic and heavy gas leakage accidents have the characteristics of suddenness and seriousness of the damage.An optimal scheduling model with multiple demand points,multiple supply points and multiple material types with the goal of minimizing emergency total time and total emergency cost was established.In order to enhance the practicability of the model,vehicle load and optimal path selection were added.The improved Dijkstra algorithm was used as a sub-algorithm of multi-objective partical swarm optimizition(MOPSO)to solve the model.Aiming at the weakness of MOPSO algorithm that was easy to fall into local optimal solution,the update mode of inertia weight is designed to enhance the global search ability of the algorithm.Meanwhile,the adaptive grid method was used for reference in particle selection operation,which enriched the diversity of particle swarm.Finally,simulation experiment were performed to verifies the effectiveness of the proposed model and algorithm.
作者
李志颖
杨宏兵
秦萍
倪静
LI Zhi-ying;YANG Hong-bing;QIN Ping;NI Jing(School of Mechanical and Electric Engineering,Soochow University,Suzhou 215137,China)
出处
《科学技术与工程》
北大核心
2019年第32期307-312,共6页
Science Technology and Engineering
基金
国家自然科学基金(61773115)
苏州市产业技术创新专项(SS201704)
2017年度大学生创新创业训练计划(2017xj044)资助
关键词
多目标粒子群优化算法
有毒重气泄漏
应急资源调度
路径选择
多目标优化
multi-objective partical swarm optimizition(MOPSO)algorithm
toxic heavy gas leakage
emergency resource scheduling
path selection
multi-objective optimization
