计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
16期
226-231
,共6页
应急物资%储备库%选址-配给模型%多目标优化%遗传算法
應急物資%儲備庫%選阯-配給模型%多目標優化%遺傳算法
응급물자%저비고%선지-배급모형%다목표우화%유전산법
emergency materials%reserve depot%location-allocation model%multi-objective optimization%genetic algorithm
为整合区域性应急物资储备资源,加强储备物资的协同管理,研究了区域性应急物资储备库的多点选址-配给问题。建立了以储备库建设成本与变动成本、物资运输成本之和最小化,以及物资运输总时间最小化的区域性应急物资储备库选址-配给多目标优化模型。鉴于多品种、多目标选址-配给问题的特点,设计了一种改进的多目标遗传算法,并用MATLAB编程实现模型的求解。在算法流程设计中,对于高维稀疏矩阵编码且具有强约束限制的选址-配给问题,初始化过程中采取搜索空间限定法来规避违约,并设计了定位变异算子以此生成子代。算例分析结果表明该算法性能较好,可以有效求解多点设施选址-配给问题。
為整閤區域性應急物資儲備資源,加彊儲備物資的協同管理,研究瞭區域性應急物資儲備庫的多點選阯-配給問題。建立瞭以儲備庫建設成本與變動成本、物資運輸成本之和最小化,以及物資運輸總時間最小化的區域性應急物資儲備庫選阯-配給多目標優化模型。鑒于多品種、多目標選阯-配給問題的特點,設計瞭一種改進的多目標遺傳算法,併用MATLAB編程實現模型的求解。在算法流程設計中,對于高維稀疏矩陣編碼且具有彊約束限製的選阯-配給問題,初始化過程中採取搜索空間限定法來規避違約,併設計瞭定位變異算子以此生成子代。算例分析結果錶明該算法性能較好,可以有效求解多點設施選阯-配給問題。
위정합구역성응급물자저비자원,가강저비물자적협동관리,연구료구역성응급물자저비고적다점선지-배급문제。건립료이저비고건설성본여변동성본、물자운수성본지화최소화,이급물자운수총시간최소화적구역성응급물자저비고선지-배급다목표우화모형。감우다품충、다목표선지-배급문제적특점,설계료일충개진적다목표유전산법,병용MATLAB편정실현모형적구해。재산법류정설계중,대우고유희소구진편마차구유강약속한제적선지-배급문제,초시화과정중채취수색공간한정법래규피위약,병설계료정위변이산자이차생성자대。산례분석결과표명해산법성능교호,가이유효구해다점설시선지-배급문제。
The multi-depot location-allocation problem of regional reserve depots of emergency materials for integration and collaborative management of reserve resources is studied. A multi-objective location-allocation model for regional reserve depots of emergency materials is developed to minimize the sum of fixed and variable costs of reserve depots and transportation costs, as well as the total transportation time of emergency materials. According to the characteristics of multi-commodity, multi-objective location-allocation problem, an improved genetic algorithm is proposed and pro-grammed by using MATLAB to solve the model. As for the location-allocation problem with high-dimensional sparse matrix-based encoding and strong constraints, search space constraint strategy is adopted in the initialization, and the ori-entation mutation operator is developed to generate offspring individuals. Finally, numerical results show that the algo-rithm is effective and feasible in solving the above multi-facility location-allocation problem.