基于改进粒子群算法的异质车队二级IRP优化

针对供货商管理库存（Vendor Managed Inventory,VMI）模式下的二级库存路径问题（Inventory Routing Problem,IRP）,结合需求的波动特征,以二级库存路径问题系统总成本最小化为目标,建立异质车队的二级库存路径问题混合整数规划模型,并设计改进的粒子群算法对模型求解。数值实验分析验证了模型和算法的适用性和有效性,结果显示,使用异质车队不仅可以提高配送车辆的装载率,降低零售商的库存水平,还会减少二级库存路径问题系统总成本;敏感性分析表明,不论需求波动程度怎样变化,使用异质车队时二级库存路径问题系统总成本都会得到降低。     

生鲜产品的纯电动冷藏车配送路径问题研究

根据生鲜产品和纯电动冷藏车的特性，研究了供应商使用同一车型的纯电动冷藏车给需求多样化的零售商配送生鲜产品的路径优化问题，考虑了车辆在行驶途中可以多次前往充电站充电以及零售商对于被服务时间的要求，以总配送成本最小为目标，构建了有客户软时间窗约束和车辆里程约束的生鲜产品配送路径问题的数学模型，以Solomn标准算例为基础构造算例，并设计了蚁群算法对模型进行求解，得到了包括充电计划在内的车辆路径方案，并与传统冷藏车配送路径方案相比较，结果发现两种方案的总成本相差不大，纯电动冷藏车虽然路线长度更长，但是可以减少温室气体的排放，运输成本较低，并且享有政府补贴，更加符合供应商的需求。     

供应链环境下带越库配送的多配送中心车辆路径问题

从零售业纵向供应链管理入手,考虑由供应商、零售商和多个配送中心构成的城市物流协同配送网络,研究带有越库配送的多配送中心车辆路径问题.分析越库配送的实施要求和操作准则,将配送过程分为集货、送货阶段.应对产品种类多样化需求,设置集货过程车辆协同作业返回配送中心,送货过程需求可拆分的运作机制.以最小化车辆运输成本和操作成本为目标,建立多配送中心车辆路径问题优化模型.针对模型特性设计改进遗传算法进行求解.最后通过仿真实例验证模型的可行性和算法的有效性, 结果表明,越库配送模式能有效服务城市区域零售门店的及时供货,在配送时间和运输成本方面具有显著优势.     

多物流中心共同配送的车辆路径问题研究

研究多物流中心共同配送的车辆路径问题。首先考虑客户服务关系变化与客户需求的异质性情况,设计一种共享客户需求、配送车辆与物流中心的共享物流模式;再综合考虑车辆容量、油耗、碳排放、最长行驶时间、客户需求量与服务时间等因素,以总成本最小为目标构建多物流中心共同配送的车辆路径规划模型,并设计一种改进蚁群算法进行求解;最后采用多类型算例进行仿真实验,结果表明共享物流模式能有效避免交叉配送与迂回运输等不合理现象,降低物流成本,缩短车辆行驶距离,减少车辆碳排放,促进物流与环境的和谐发展。     

基于鲁棒优化的供应链联合补货策略

供应链管理中的客户需求不确定性会导致需求信息偏差逐级放大的"牛鞭效应",但目前常用的供应链管理策略为供应商管理库存,没有考虑需求不确定的影响。为此,在单个供应商、多个零售商需求不确定的情况下,结合鲁棒优化法提出一种联合补货策略进行库存管理。构建一个非线性混合整数规划模型以计算两级供应链的总成本,通过总成本的变化来反映供应链系统的性能,采用鲁棒优化法求解供应链系统的最小总成本,并使用外部和内部两层迭代算法获得供应商和零售商的补货周期及补货数目。实验结果表明,与传统的供应链策略ERI和AR相比,该策略可有效降低供应链系统的总成本。     

需求可拆分的汽车零部件循环取货路径优化研究

为了降低汽车零部件入厂物流的总成本,针对汽车零部件入厂物流的循环取货路径规划问题,提出将供应商集货需求拆分配送的改进数学模型,以最小化运输和库存总成本为目标函数,并且满足时间窗和车辆容量的限制。通过设计禁忌搜索算法求解,并根据模型的特点对初始解及邻域搜索方法进行改进。最后应用实验数据验证算法有效性,并与其他算法对比,结果表明通过需求拆分可以节约运输成本并提高车辆装载率。     

不确定需求下快递配送网络鲁棒优化

“双十一”期间,分拨中心“爆仓”现象表明：确定需求下的车辆路径不适合解决需求激增的配送问题。以需求确定模型为基础,构建基于情景集的鲁棒优化研究模型,并根据变化的快件数量,重新分配客户服务时间;通过计算每条路径的旅行时间,在满足时间窗的基础上,实现对自有车辆的最大利用。改进蚁群算法利用Matlab求解,分析发现：优先考虑运输时效所产生的成本与成本最优值存在较小差距,但总旅行时间优势明显;公司规模与业务量和总成本之间存在相关性,业务量增加并不会引起利润快速增长。     

两级系统多周期随机库存路径优化

库存和运输是物流活动的最主要环节,如何同时对二者进行优化,是供应商管理库存必须解决的核心问题。针对一个配送中心为多个零售商实施统一配送的两级系统,以最小化系统计划期平均总费用为目标,分析包括零售商存储费、缺货费,以及配送中心进货费、存储费和配送费的系统全部费用组成,整合库存与配送建立了库存路径问题数学模型。根据零售商需求的随机性和库存路径问题本身的两阶段性,估计零售商库存上下限,选择配送中心订货策略及配送优先原则,借鉴旅行商问题求解思路,设计了求解问题的启发式算法。用Matlab7.0编程实现仿真算例求解表明,整合优化比分别优化节省平均总费用6.2%。     

考虑拥堵区域的多车型绿色车辆路径问题优化

针对降低物流配送过程中产生的碳排放问题,从绿色环保角度出发,提出一种考虑交通拥堵区域的多车型物流配送车辆的绿色车辆路径问题（GVRP）。首先分析不同类型车辆、不同拥堵状况对车辆行驶路线规划的影响,然后引入基于车辆行驶速度和载重的碳排放速率度量函数;其次以车辆管理使用费用和油耗碳排放成本最小作为优化目标,构建双目标绿色车辆路径模型;最后根据模型的特点设计一种融合模拟退火算法的混合差分进化算法对问题进行求解。通过实验仿真验证模型和算法可以有效规避拥堵区域,与只使用单一4 t车型配送相比,所提模型总成本降低了1.5%,油耗碳排放成本降低了4.3%;和以行驶距离最短为目标的模型相比,所提模型的总配送成本降低了8.1%。说明该模型提高物流企业的经济效益也促进了节能减排。同时所提算法与基本差分算法相比,总配送成本可以降低3%~6%;与遗传算法相比,优化效果更明显,总配送成本可以降低4%~11%,证明该算法更具有优越性。综上所提模型和算法可以为物流企业城市配送路径决策提供良好的参考依据。     

具单周期特性的短生命周期产品随机IRP及算法

为优化企业物流系统,针对单周期,短生命周期产品的特点,将库存控制与配送路径安排决策集成,考虑随机需求、缺货成本、积压贬值成本、配送成本等,建立一个具有单周期特性的短生命周期产品随机IRP离散模型,目标是合理确定各零售门店的订购数量及配送路线使得系统成本最小。该问题属于NP-hard问题。对此,采用“报童模型”和差分法求解最佳订购量,将模型予以转化,并设计了一种遗传算法进行求解。算例结果表明所提算法能在较短时间内求解出不同客户数目组合的满意解。结论是：门店订购量宜采用组合选择方式;系统成本与单位行程运价正相关;车容量增大有助于降低系统成本。     

考虑供应商选择的选址一库存一路径的联合优化

针对装配型制造企业供应链集成优化问题,建立了随机需求情形下整合供应商选择和各层级之间运输方式选择的多层级选址—库存模型。该模型通过对供应商的选择,装配厂和分销中心的选址,相邻两层级之间的分配服务关系及运输方式的确定,实现整体供应链网络成本最小化。为求解此混合整数非线性规划模型,设计了一种矩阵编码的改进自适应遗传算法。仿真实验表明,该算法的解的寻优能力明显优于标准遗传算法,得出了供应链总成本与装配厂的最大提前期存在一定规律性的结论。     

Inventory control model for a supply chain system with multiple types of items and minimum order size requirements

This paper considers a replenishment problem for a single buyer who orders multiple types of items from two or more heterogeneous suppliers in order to sell to end customers. The buyer periodically orders each type of item from the suppliers according to a select inventory control policy. Processing the order, each supplier enforces the policy that an order from the buyer must meet a predetermined minimum order quantity (MOQ). Therefore, the buyer must decide how much to order from each supplier considering the current inventory level, demand forecast, and MOQ requirement. The buyer's problem is formulated as an integer programming model and an efficient implementation strategy is suggested to apply the model to real problems. Numerical experiments are performed to test the validity of the proposed model as well as the efficiency of the implementation strategy. The experimental results show that this model combined with the implementation method yields a considerable cost reduction compared to the most efficient policy currently available.     

Inventory lot-sizing with supplier selection

This paper presents a multi-period inventory lot-sizing scenario, where there are multiple products and multiple suppliers. We consider a situation where the demand of multiple discrete products is known over a planning horizon. Each of these products can be sourced from a set of approved suppliers, a supplier-dependent transaction cost applying for each period in which an order is placed on a supplier. A product-dependent holding cost per period applies for each product in the inventory that is carried across a period in the planning horizon. The decision maker needs to decide what products to order in what quantities with which suppliers in which periods. An enumerative search algorithm and a heuristic are presented to address the problem.     

Incorporating lateral transfers of vehicles and inventory into an integrated replenishment and routing plan for a three-echelon supply chain

This paper focuses on developing an integrated replenishment and routing plan that takes into account lateral transfers of both vehicles and inventory for a three-echelon supply chain system including a single plant, multiple distribution centers and multiple retailers. A mixed integer programming model to the overall system is formulated first, and then an optimization-based heuristic consisting of three major components is proposed. The purpose of the first component is to assign retailers to distribution centers, and determine routing schedules for each distribution center. And the remaining two components are corresponding to two smaller optimization models – a variant of the classical transportation problem modeled for determining vehicle transfer between distribution centers, and a variant of the conventional minimum cost network flow problem modeled for determining inventory replenishment and transfer. Experimental results reveal that the proposed algorithm is rather computational effectiveness, and the pooling strategy that considers both vehicles and inventory transfers is a worthy option in designing supply chain operations.     

Capacity-constrained supplier selection model with lost sales under stochastic demand behaviour

In today’s market conditions, volume of demand is quite uncertain and thus it is hard to estimate. In many cases, buyer is prone to use supply chain flexibility rather than inventory holding strategy to withstand demand uncertainty. We assume that the buyer releases a replenishment order to the supplier for each cycle (or period) under the contract which is mainly composed of four parameters: (1) supply cost per unit, (2) minimum order quantity, (3) order quantity reduction penalty and (4) maximum capacity of the supplier. Based on these parameters, there are two flexibility options that buyer should evaluate in the order of cycle (1) issue an order smaller than the minimum order quantity and pay the related penalty and (2) place no order and lose the sales. Hence, Q _lost emerges as a critical buyer decision, the order quantity, below which no order is placed. Total expected supply cost plus lost sales, as a function of Q _lost is presented. We derive the optimal Q _lost that minimises the total cost function. Since capacity of each supplier is finite, we then develop a supplier selection model with total cost minimisation over the suppliers subject to capacity constraint that has a stochastic nature stemming from demand behaviour. Linearisation on the model is performed using chance-constrained programming approach. From a given set of supply bids from the potential supply chain partners, the buyer is able to make a quantifiable choice.     

随机需求下的供应链库存控制策略研究

考虑了由多个供应商、一个配送中心组成的二级供应链系统在市场需求为随机情况下的多品种库存问题。通过确定各变量之间的关系,以配送中心损失期望值最小为目标函数,建立了一个混合整数非线性规划模型;利用求解多元函数条件极值的办法来求解该问题模型;最后给出了一个算例进一步诠释了该解法,从而丰富了在面对市场为随即需求下的多品种库存控制策略的研究工作。     

An integrated fuzzy-lp approach for a supplier selection problem in supply chain management

In supply chain management process, the firm select best supplier takes the competitive advantage to other companies. Thus, supplier selection is an important issue and with the multiple criteria decision-making approach, the supplier selection problem includes both tangible and intangible factors. This paper is aimed to present an integrated fuzzy and linear programming approach to the problem. Firstly, linguistic values expressed in trapezoidal fuzzy numbers are applied to assess weights and ratings of supplier selection criteria. Then a hierarchy multiple model based on fuzzy set theory is expressed and fuzzy positive and negative ideal solutions are used to find each supplier’s closeness coefficient. Finally, a linear programming model based on the coefficients of suppliers, buyer’s budgeting, suppliers’ quality and capacity constraints is developed and order quantities assigned to each supplier according to the linear programming model. The integrated model is illustrated by an example in a textile firm.     

A holonic approach based integration methodology for transportation and warehousing functions of the supply network

The supply chain (SC) is often defined as a network that is composed of different functions, including suppliers, manufacturing plants, warehouses/distribution centers, retailers and customers. A supply network (SN) is a sequence of different and multiple numbers of functions and individual functional units that must satisfy all capacities and demand requirements imposed by customers with minimum cost to the network. The most important functions of a SN are warehousing and transportation functions. This paper addresses the warehousing and transportation network design problem that involves determining the best strategy for distributing the sub-products from the suppliers to the warehouse and from the warehouse to the manufacturers. Considering some similarities between holonic systems and SN systems, a holonic approach based modeling methodology is proposed in this study. A multiple supplier, single warehouse and multiple manufacturer system are considered to be an integrated warehousing and transportation network. Consequently, a linear programming model is presented to maximize the profit of both of the overall SN and the individual functional units of the SN functions.     

A mathematical model for order splitting in a multiple supplier single-item inventory system

In this paper we develop a mathematical model which considers multiple-supplier single-item inventory systems. The lead times of the suppliers and demand arrival rate are random variables. All shortages are backordered. Continuous review (s, Q) policy has been assumed. When the inventory level hits the reorder level, the total order is split among n suppliers. The problem is to determine the reorder level and order quantity for each supplier so that the expected total cost per time unit, including ordering cost, procurement cost, inventory holding cost and shortage cost is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared to the relevant models in the literature. In addition, some managerial insights are observed.