管理科学
管理科學
관이과학
Management Sciences in China
2008年
5期
111~120
,共null页
干扰管理 扰动恢复 车辆路径问题 时间窗 容量 遗传算法
榦擾管理 擾動恢複 車輛路徑問題 時間窗 容量 遺傳算法
간우관리 우동회복 차량로경문제 시간창 용량 유전산법
disruption management; disruption recovery; vehicle routing problem; time window; capacity constraint; genetic algorithm
为解决由顾客需求变化引发的物流配送干扰问题,提出基于干扰管理思想构建扰动恢复策略和方案。应用虚拟多车场实现车辆调度扰动恢复问题转化,提出车辆调度扰动恢复策略和扰动度量方法,以作为车辆调度干扰管理建模的基础;分析顾客时间窗和发货量变化造成的扰动并进行辨识,建立相应的干扰管理模型,提出归一化处理办法对VRPTW、MD-VRPTW和MDVRPTW干扰管理问题进行有效兼容;结合干扰管理模型的特点,改进基于顾客的编码表示方法,可以反映出车辆调度扰动恢复策略;根据干扰管理思想,设计遗传算法对干扰管理模型进行求解。给出了一个具有代表性的算例试验结果,算例结果及其分析表明干扰管理模型和遗传算法的有效性。
為解決由顧客需求變化引髮的物流配送榦擾問題,提齣基于榦擾管理思想構建擾動恢複策略和方案。應用虛擬多車場實現車輛調度擾動恢複問題轉化,提齣車輛調度擾動恢複策略和擾動度量方法,以作為車輛調度榦擾管理建模的基礎;分析顧客時間窗和髮貨量變化造成的擾動併進行辨識,建立相應的榦擾管理模型,提齣歸一化處理辦法對VRPTW、MD-VRPTW和MDVRPTW榦擾管理問題進行有效兼容;結閤榦擾管理模型的特點,改進基于顧客的編碼錶示方法,可以反映齣車輛調度擾動恢複策略;根據榦擾管理思想,設計遺傳算法對榦擾管理模型進行求解。給齣瞭一箇具有代錶性的算例試驗結果,算例結果及其分析錶明榦擾管理模型和遺傳算法的有效性。
위해결유고객수구변화인발적물류배송간우문제,제출기우간우관리사상구건우동회복책략화방안。응용허의다차장실현차량조도우동회복문제전화,제출차량조도우동회복책략화우동도량방법,이작위차량조도간우관리건모적기출;분석고객시간창화발화량변화조성적우동병진행변식,건립상응적간우관리모형,제출귀일화처리판법대VRPTW、MD-VRPTW화MDVRPTW간우관리문제진행유효겸용;결합간우관리모형적특점,개진기우고객적편마표시방법,가이반영출차량조도우동회복책략;근거간우관리사상,설계유전산법대간우관리모형진행구해。급출료일개구유대표성적산례시험결과,산례결과급기분석표명간우관리모형화유전산법적유효성。
To tackle the disruption that is caused by the demands of customers in the logistics, the paper proposes disruption recovery strategies and solutions based on the theory of disruption management. The trans-formation method for the disruption recovery of the vehicle routing problem is put foward on the basis of the multiple depots, and the disruption recovery strategies and the methods of deviation measurement are given, which is the foundation of the disruption management modeling for the vehicle routing problem. After the disruption is illustrated and distinguished by analyzing and identifying the changes of time windows and delivery weight of customers, the disruption management model is constructed, and the normalization method for the model is given, making the model compatible with VRPTW, MDVRPTW and disruption management for MDVRPTW. On the basis of the characteristic of the model, the chromosome code based on customer is ameliorated, which can indicate the disruption recovery strategies; according to the disruption management, the genetic algorithm is designed to solve the model. The representative result and analysis are provided in this paper, and the experiment indicates the validity of the model and algorithm.