考虑横向转运的线状需求物流节点选址研究

铁路线路建设需要大量物资,沿拟建线路布局物流节点对成本控制具有重要意义。为决策物流节点的位置及其相应的服务区域,考虑拟建线路物资需求的不确定性,引入物流节点间的横向转运策略,以运营总成本最小为目标,建立了线状需求下的设施选址−库存模型。在分析模型性质的基础上,设计了基于线搜索的求解算法。算例分析表明,横向转运增加一定的转运成本和运输成本,但大幅降低了物流节点的库存成本,进而降低运营总成本,考虑横向转运对物流节点的选址和服务区域决策有一定的影响。     

多阶段灾后救援选址-路径模型及求解算法

配送中心选址与配送车辆路径安排的集成优化对灾后应急救援至关重要,综合考虑救援物资多次运达、多阶段持续配送等特点,以各救援物资需求点间运达时间之和以及系统总反应时间最小为目标,建立一种多阶段带时间约束的应急救援物资配送选址-路径优化模型。为模型的求解,设计一种特定的LRP路径编码,根据编码的结构独立、路径间相互关联等特点,引入一种适应匹配交叉算子,同时结合稳定均衡策略设计一种均衡协作启发式算法(BGEA算法)。为了验证模型的有效性及BGEA算法求解选址-路径多目标问题的优越性,对算例作求解分析,得出了可行性调运方案,并将BGEA算法求解性能与已知算法求解性能进行对比,比较结果表明BGEA算法求解该问题具有良好的寻优能力。     

一种军事物流配送中心的选址模型

考虑战场保障网络中军事物流配送中心到部队用户的时间约束对军事物流配送中心选址的影响,针对战场保障网络中节点间存在多重边的情况,通过逐步搜索避免形成环,剪除超过时间约束的路径,构造了可行路径算法,该算法可以在(n-1)步内完成搜索.根据各条边的时间可靠性进行了路径筛选,建立了军事物流配送中心的选址-路线安排模型.     

基于成本/收益权衡的多元需求FIP选址研究

需求种类分析对选址决策至关重要,考虑了消费者需求种类为多元化,且各类需求间有影响的网络上截流(FIP)选址问题,引入路径上需求损失函数,建立了收益最大和总的建设成本最小的双目标的多元需求FIP(mDFIP)的新模型。所建立的模型为NP-hard问题,设计了多目标演化算法求解模型,最后通过具体的算例与基于ε约束法的分支定界法进行比较,结果表明在求解效率上多目标演化算法具有很大优势。     

基于物流能力优化的配送中心选址问题研究

通过分析配送中心的选址对第三方物流企业的发展有着重要影响,提出了配送中心的选址应该以提高物流企业的物流能力为目标,而物流能力是一个综合指标,因此基于物流能力优化的配送中心选址模型是多目标的,在模型求解中,利用带自适应移动线的遗传算法来权衡多目标函数.     

基于贪心遗传的地下物流节点选择规划研究

以国内某地区物流概况为研究背景,结合国内外地下物流系统研究成果,将集合覆盖的思想引入地下物流网络节点选址规划,建立以物流节点数量最少及物流节点转运率最低为优化目标的双层多目标规划模型,并结合贪心算法和遗传算法进行优化求解。研究表明：通过将集合覆盖的思想对城市地下物流系统节点规划进行初步探讨是可行有效的;基于贪心遗传算法进行优化求解,使得该地区地下物流网络节点选择达到全局最优,有效控制了物流节点的数量及节点转运率的大小;地下物流网络节点表现出明显的区域集中性,即服务节点均集中在物流需求点附近,且二级节点服务区域总是邻近某个一级节点。     

第三方物流联盟中物流任务的优化调度

为了提高物流服务水平、降低物流运作成本,针对由多个第三方物流服务商组建而成的第三方物流联盟中物流任务与物流服务资源的优化调度问题展开研究,综合考虑各第三方物流服务商资源节点提供物流活动服务成本和物流服务总时间,以时间最短和成本最低为优化目标,提出了基于时间和成本的多目标优化调度模型,针对目前物流任务调度优化模型中只考虑各物流服务资源节点本身的服务成本和时间,而未考虑执行各个物流活动之间的物流资源节点之间的衔接时间与衔接成本的问题,提出一种计算不同物流服务资源节点之间的物流服务衔接时间和衔接成本的方法,在模型中,考虑了物流资源服务时间窗限制问题.最后提出了一个改进的遗传算法进行模型求解,并通过算例验证了研究的有效性.     

引入补偿、惩罚策略的配送中心选址问题研究

根据配送中心与零售商在市场中的相对地位,针对保持市场份额或降低物流成本不同目标,配送中心对远距离零售商可制定补偿或惩罚两种策略。在LMRPVCC问题优化模型基础上,在目标函数与约束条件中引入运输补偿、惩罚成本项及服务半径Dr,可将模型扩展为引入补偿、惩罚策略的LMRPVCC选址-库存问题的非线性整数规划模型。利用所设计的粒子群算法对Hakimi文章中10节点算例和Daskin和Shen的文章中的49节点求解,对惩罚、补偿系数W、服务半径Dr进行敏感性分析的结果表明,不同配送策略对配送中心物流总成本、各分项成本以及配送中心满意区位有重要影响。     

基于NSGA-Ⅱ算法的正逆向物流网络中回收处理中心选址

为保护环境和减少运输成本,对回收处理中心选址问题的研究应考虑多目标。本文从政府和企业两个角度出发,提出正逆向物流网络中回收处理中心的选址问题。将货物运输过程中产生的碳排放进行量化,并为本文研究的选址问题构建了双目标模型,使结果达到经济目标和环境目标的有效平衡。采用Lingo软件和NSGA-Ⅱ算法两种方法对双目标模型进行求解。最后,以大连市为例进行数值分析,并对NSGA-Ⅱ算法的求解结果进行灵敏度分析,验证算法的可行性与求解的稳定性。     

煤炭物流园区多目标动态选址

为了有效整合物流资源,实现不同周期物流园区配送总成本和负效用的降低,构建了以煤炭物流网络总成本最小和对大气以及居民产生负效用最低为目标,多目标多周期煤炭物流园区的动态选址模型,并采用Lingo11.0进行多次迭代求解,最终得到全局最优解。以山西阳煤集团2014年实际的销售和运输数据为依据,选取了6个候选物流园区,18个需求客户,针对4个不同周期物流园区的选址和配送进行了差异化决策,使得成本节约了35%,最终验证了模型的科学性。     

需求和供应不确定下的选址研究

在需求不确定的同时,考虑了由于意外事件导致设施失灵而造成的供应不确定性,提出了这两个不确定因素下的设施选址模型.已知各个设施的失灵风险概率,通过情景规划描述需求不确定性,在保证供应系统的稳定性和鲁棒性不低于既定值的情况下,使得运输费用和设施失灵不能提供服务时的风险费用之和最小,提出了拉格朗日松弛算法,并通过大量算例验证...     

Demand point aggregation analysis for a class of constrained location models: a penalty function approach

Many location models involve location cost functions that depend on the distances between demand points and new facility locations. There can be so many demand points that they must be aggregated to obtain a tractable model. We consider a class of such problems where the location cost functions appear in both the objective and the constraints. By using the concept of a penalty function we obtain error bounds, that is, upper bounds on the errors introduced by aggregation. The error bounds can be used to drive demand point aggregation schemes, and consider both objective error and constraint error.     

多级库存控制的连锁经营企业配送网络设计

研究了随机需求条件下连锁经营企业配送网络设计及其库存决策的联合优化问题.详细分析了基于POT(power of two)多级库存控制策略的连锁企业多级工作库存及订货成本,给出了门店及配送中心在满足给定服务水平条件下的安全库存成本.在综合考虑运输成本和配送中心选址成本的基础上,建立了以系统总成本最小为目标的配送系统总成本优化模型,并采用遗传算法求解该优化模型,在得到最优配送网络设计方案的同时,确定了配送中心订货周期及门店配送周期.通过算例验证了模型及算法的有效性,并分析了需求、运输距离和选址成本等因素的变化对系统总成本的影响,为连锁经营企业的物流配送网络设计及库存控制提供决策支持.     

考虑高铁时间窗和客户满意度的生鲜品公铁联运路径选择

针对生鲜品小批量、高时效的运输特点,提出将“高速公路+高速铁路”作为一种快速联运方式应用于生鲜品的多式联运中。以总成本最低为目标,以高铁服务时间窗、客户满意度为约束,构建基于模糊需求的生鲜品公铁联运路径选择与运输方式组合模型。以“哈尔滨-昆明”联运网络为例进行算例分析,应用Lingo12.0实现模型求解。结果表明,提出的“高速公路+高速铁路”联运方式在运输总成本和客户满意度方面均优于单一运输方式,且与“高速公路+航空”联运方式相比具有成本优势;采用灵敏度分析法,分别探究了置信水平、客户品质满意度约束值和时间满意度约束值的变化对运输总成本的影响关系,同时验证了模型的有效性,为“高速公路+高速铁路”方式下的生鲜品运输路径选择提供有益参考。     

基于灰色聚类评估的配送中心选址模糊多目标优化模型

将多属性决策方法与最优化方法相集成,研究了多配送中心选址优化问题。首先采用灰色聚类决策计算各候选地定性属性的综合评估值。再以选定配送中心的评估值均值最大化、系统成本最小化,以及配送中心容量利用率最大化作为3个优化目标,建立一个考虑需求点模糊需求、供应点与候选配送中心容量限制的三级供应链系统多配送中心选址模型。该模型被描述成了一个多目标的非线性混合整数规划模型。采用机会约束规划对模糊需求进行清晰化处理,并应用目标加权的方法将问题转化为单目标问题。通过算例验证了所提模型的可行性。在实际工作中,可根据决策者权重偏好得出令人满意的结果。     

A robust optimization approach for the capacitated vehicle routing problem with demand uncertainty

In this paper we introduce a robust optimization approach to solve the Vehicle Routing Problem (VRP) with demand uncertainty. This approach yields routes that minimize transportation costs while satisfying all demands in a given bounded uncertainty set. We show that for the Miller-Tucker-Zemlin formulation of the VRP and specific uncertainty sets, solving for the robust solution is no more difficult than solving a single deterministic VRP. Our computational results on benchmark instances and on families of clustered instances show that the robust solution can protect from unmet demand while incurring a small additional cost over deterministic optimal routes. This is most pronounced for clustered instances under moderate uncertainty, where remaining vehicle capacity is used to protect against variations within each cluster at a small additional cost. We compare the robust optimization model with classic stochastic VRP models for this problem to illustrate the differences and similarities between them. We also observe that the robust solution amounts to a clever management of the remaining vehicle capacity compared to uniformly and non-uniformly distributing this slack over the vehicles.     

Perturbation analysis for continuous and discrete flow models: a study of the delivery time impact on the optimal buffer level

In this paper, a manufacturing system composed of a single-product machine, a buffer and a stochastic demand is considered. Two models are presented: continuous and discrete flow models including constant delivery times, machine failures and random demands. The objective is to determine the value of the optimal buffer level, for a hedging point policy which minimises the total average cost function. The cost function is the sum of inventory, transportation and lost sales costs. Infinitesimal perturbation analysis is used for optimisation of the failure-prone manufacturing system. The trajectories of buffer level are studied for the continuous and discrete cases and the infinitesimal perturbation analysis estimators are evaluated. These estimators are shown to be unbiased and then they are implemented in an optimisation algorithm which determines the optimal buffer level in the presence of constant delivery time. Numerical results are presented for continuous and discrete flow models and then compared in order to evaluate the application of the infinitesimal perturbation analysis on the discrete flow model.     

Assembly system facility design

This paper addresses the design of an assembly system facility consisting of multiple assembly lines of different shapes. In such a design problem there are two conflicting objectives: (i) to minimize the overall area of the facility; and (ii) to maximize the efficiency of the material handling transportation system. We first address the optimization problem of objective (ii) when replacing objective (i) with a constraint on the facility area. We propose a mixed-integer linear program to determine the layout of a facility with given dimensions and with given assembly line areas and shapes (that cannot be changed due to technological considerations). In the layout model, the physical placement of each line within the facility is a decision variable. The objective function of the layout model is to minimize the distances traveled by material flow. Our performance analysis provides an indication of the maximal problem size that can be solved in a reasonable amount of time and we examine the effect of the problem parameters on the solution run time. This layout model is then incorporated into an efficiency frontier approach for facility design to address both objectives. Examples are presented to illustrate the use of the proposed facility design model.     

Positioning empty containers among multiple ports with leasing and purchasing considerations

With the recent development of container transportation, the imbalance of empty containers among ports has become more serious. We consider the problem of positioning empty containers. The goal of this study is to propose a plan for transporting empty containers between container ports (terminals) to reduce the imbalance. There is currently a demand at each port and any backlog of containers is not permitted. The objective is to minimize the total relevant costs such as transportation cost, handling cost, and holding cost, etc. In this study, we develop a model with respect to the leasing and purchasing of containers. Mixed integer programming and genetic algorithms are used to solve the model. A hybrid GA is also proposed to reduce the computation time while still obtaining an acceptable result.