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针对不确定环境下托盘共用系统托盘调度问题,建立托盘生产、库存和运输等能力受限条件下的托盘调度多目标优化模型.该模型将托盘共用系统网络细分为托盘生产/维修—调度/再调度—回收三个过程,并满足托盘调度系统运作成本最低、惩罚成本最低及模型鲁棒性最高等多个相互冲突的运作目标,对网络各环节主体存在的不确定因素,从模型鲁棒性的角度出发,构建各不确定因素的鲁棒性控制指标;最后给出基于遗传算法的求解过程.算例结果表明,与不添加鲁棒约束的优化模型相比,该模型能有效控制不确定因素的负影响,增加托盘调度决策的稳定性,论文还对三个优化目标之间的影响关系进行分析,得到一些有意义的结论.“,”To solve pallet allocation problem in pallet pool under uncertain environment,this paper establishes a multiobjective pallet allocation optimization model with constraints of manufacturing,inventory and transportation capacity and so on.In this model,the pallet pool network is divided into,manufacturing/maintenance-distribution/reposition-recovery,three process,and considering the lowest cost of system operation,the lowest penalty cost and the highest robust of model,which are three multiple conflicting operation targets.In addition,the robust restraint target is defined according to every uncertain factor.Finally,genetic algorithm for solving this model is presented.In comparison with optimization model which is not constrained,the example results show that this model can actively control and weaken the negative in fluence of uncertain factors and increase the pallet allocation stability,and the relationship of three objectives is analyzed.