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动态需求下的多周期动态应急资源调度问题研究

发表时间:2018-07-13  浏览量:892  下载量:106
全部作者: 刘静,周亚稳,张宇瞳,郝星星
作者单位: 西安电子科技大学智能感知与图像理解教育部重点实验室
摘 要: 紧急救援中存在多种不确定因素,使得这一过程具有动态变化的特点。受灾地区的物资需求在调度过程中可能是动态变化的,同时在应急资源调度(emergency resource scheduling,ERS)之前,收集到的受灾地区的需求信息可能不能真实反映需要。本文提出一种针对不确定需求下多周期动态应急资源调度的多目标优化模型。在这一模型中,考虑了三种动态调整情景来根据实时灾区资源需求信息及时调整调度方案。为得到最优调度方案,使用了一种带有差分进化算子的基于分解的多目标进化算法(multi-objective evolutionary algorithm based on decomposition with differential evolution,MOEA/D-DE)来求解这一问题。并通过实验展示动态调整方法的作用方式,同时验证了提出算法的有效性。
关 键 词: 运筹学;应急资源调度;多周期规划;动态需求;多目标进化算法
Title: Multi-period dynamic emergency resource scheduling problems under dynamic demand
Author: LIU Jing, ZHOU Yawen, ZHANG Yutong, HAO Xingxing
Organization: Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University
Abstract: Various uncertain factors in disasters lead to the dynamic characteristics of emergency rescue. Demand of disaster areas may change dynamically during the emergency scheduling, and the information about the demand of disaster areas collected before the emergency resource scheduling (ERS) may not accurately reflect the actual demand. In this paper, a multi-objective optimization model for multi-period dynamic emergency resource scheduling problems under dynamic demand is proposed. In this model, three dynamic adjustment scenarios are considered to adjust the scheduling schemes in time according to the real-time information about the dynamic demand of resources in disaster areas. To obtain the optimal scheduling scheme, a multi-objective evolutionary algorithm based on decomposition with differential evolution (MOEA/D-DE) is introduced to solve the problem. Experiments are conducted to show how the dynamic adjustment methods work and validate the effectiveness of the proposed algorithm.
Key words: operational research; emergency resource scheduling; multi-period planning; dynamic demand; multi-objective evolutionary algorithm
发表期数: 2018年7月第13期
引用格式: 刘静,周亚稳,张宇瞳,等. 动态需求下的多周期动态应急资源调度问题研究[J]. 中国科技论文在线精品论文,2018,11(13):1328-1344.
 
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