同时集散货物的开放式车辆路径问题研究

本文研究了车辆工作时间限制下同时集散货物的多配送中心开放式车辆路径问题,以车辆数和运输里程最小为目标,建立了多目标规划模型,提出了基于拉格朗日松弛技术和禁忌搜索算法的混合求解算法。 该算法首先求出最优解的最大下界,然后采用客户点的分配和调整策略实现解的可行化,其中禁忌搜索引入了4种领域搜索方法,采用了随机变领域搜索方法和重起策略。算例分析表明,该算法能有效地找到满意解,且采用开放式安排路线比闭合式安排路线更加经济合理。     

基于联合配送的开放式动态车辆路径问题及算法研究

针对跨区域多配送中心多车型开放式动态联合配送问题,通过引入时间轴概念将动态问题转化为静态问题,建立考虑车载率的开放式车辆路径模型,提出多配送中心问题的整体算法和多车型的使用原则,强化物流资源整合和跨区域路径整体优化.利用云模型中云滴的随机性与稳定倾向性,改进遗传算法中交叉与变异概率的设置方式,采取“初始优化+实时优化”的两阶段求解策略,对开放式动态车辆路径问题进行实时再优化.最后,结合算例对模型和算法的有效性进行验证.     

蓄冷式多温集配路径优化模型

现实中,由于配送中心选址对占地面积、土地成本等要求较高,加之物流企业资金有限或交通拥堵等限制,配送中心的设置通常会远离市中心。为了减少集货与配送车辆往返配送中心的次数以及车辆行驶距离,本文以总成本最小化,包括车辆派遣成本、行驶成本、碳排放成本、违背时间窗的惩罚成本、保温柜/箱成本、非整箱货物的配送成本,构建了1个配送中心由大型车辆为m个供应商采用蓄冷柜/蓄冷箱集货,由1个虚拟接驳点(中型车辆)结合小型车辆为n个零售门店采用蓄冷箱多温共配的路径优化模型,并设计了基于蚁群算法的混合更新信息素策略。以20个零售门店与6个海鲜供应商的三种品温海鲜品为仿真算例,验证了模型的有效性。实例分析发现：引入虚拟接驳点的配送线路数低于单纯的配送线路数;时间窗限制越宽松,引入虚拟接驳点的优越性越突出;具有虚拟接驳点的多温集配总成本低于自配送中心的集配总成本;具有虚拟接驳点的蓄冷式多温集配尤其利于低碳环保的冷链系统构建。     

多车次同时集散货物路线问题研究

研究了配送车辆数和车辆工作时间内有限的多车次同时集散货物路线问题,以车辆数和运输里程最小为目标建立了多目标模型,提出了允许不可行解的禁忌搜索法.该方法能同时解决路线安排和路线分配的问题,其中路线安排采用了4种邻域搜索方法和重起策略,路线分配采用了初次分配和二次调整策略.算例分析表明,该方法能有效地找到满意解,且采用多车次安排路线比单车次安排路线更加经济合理.     

时间依赖型多配送中心带时间窗的开放式车辆路径问题研究

本文研究了时间依赖型多配送中心带时间窗的开放式车辆路径问题,基于道路通行情况,建立车辆行驶速度时间函数;考虑车辆载重、里程限制与客户点服务时间窗的约束,建立混合整数规划模型,目标函数为最小化车辆总成本,具体包括车辆行驶时间成本和车辆固定发车成本;提出了一种二维编码方式的混合遗传算法,针对混合遗传算法设计了多分区段单点交叉策略、动态插入算子及局部搜索策略;最后,基于Solomon VRPTW基准数据集生成27个测试算例,使用混合遗传算法进行求解。数值实验结果表明,考虑道路通行情况,选择合理的出发时间,避免拥堵时段进行配送服务,能明显减少车辆的总行驶时间,且验证了混合遗传算法能够获得问题的满意解。     

带模糊工作时间窗的多配送中心同时集散货物车辆路径问题

在线资源的特性使得配送车辆采用分时租赁的模式为客户进行服务,配送车辆路径问题呈现多模糊时间窗特性。本文构建了带有模糊工作时间窗的多配送中心同时集散货物车辆路径模型,以最小化配送成本、车辆使用数,最大化服务质量为优化目标。根据客户期望时间窗、硬时间窗、软时间窗,改进了线性梯形隶属度函数表示客户模糊满意度。模型的求解采用自适应大规模邻域搜索算法,通过引入多种群搜索机制和非支配排序操作,加快算法收敛速度、增强算法全局寻优能力。最后,通过算例求解验证模型和改进算法的有效性和优越性。     

带货物权重的车辆路径问题及遗传算法

考虑一个分销中心、多个零售商组成的分销网络系统中具有柔性车辆能力的带货物权重的车辆路径问题.并根据车辆的满载情况采用了不同的运输策略,即单点运输和多点运输方式.在多点运输方式下,与以往诸多研究不同的是,文章建立了一种基于货物权重的VRP模型——WVRP,即在安排车辆线路时每个零售商的货物需求量也作为一个因素考虑,尽可能使车辆优先供货需求量较大的零售商.最后,针对问题的性质,开发了一种基于划分的遗传算法PB-GA对问题进行求解,并与一般遗传算法及常用的启发式算法进行了分析比较.     

运力受扰的多车场车辆调度干扰管理问题研究

为解决物流配送系统中因运输车辆毁坏而产生的干扰问题,基于干扰管理思想提出了解决问题的扰动恢复策略与实施方案。在扰动度量的基础上,设计了多车场车辆调度扰动恢复策略,建立相应的干扰管理模型。针对多车场车辆调度干扰管理问题的特有属性,设计了一系列求解简化策略,有效简化了问题的求解空间。结合干扰管理模型的特点,使用改进的遗传算法进行求解。最后给出了一个算例,其结果证明了干扰管理模型与算法的有效性。     

基于Lagrange松弛分解法的供应链生产-定位-路径集成问题优化

本文研究了集成生产批量、配送中心定位和车辆运输路径问题的一个复杂大系统,并建立了相应的数学模型。为了便于理解和求解这一大系统,将这一系统运用Lagrange松弛法分解成了生产、配送中心和定位-路径等三个相对独立的子系统。基于次梯度优化算法提出了一种优化协调机制,实现了系统的整体优化,并进行了数值实验分析。     

震后应急物资多方式供应的模糊动态LRP

研究震后应急物资多方式供应中的多层次设施定位-路线规划问题(LRP),综合考虑应急物流网络中的多周期应急物资模糊需求、时间窗限制、部分路网损毁与动态恢复、车辆随机行驶时间、大需求点采用需求分割策略同时进行运输与配送等特性,以应急物资总供应时间最短为目标,构建了一个震后应急物资多方式供应的多周期模糊LRP优化模型,并根据模型特点设计了一种贪婪算法结合蚁群算法的混合启发式算法予以求解.最后,通过算例验证了本文模型和算法的可行性与有效性.     

A subsidized reverse supply chain in the Chinese electronics industry

We study a special environmental producer responsibility policy for the Chinese electronics industry that is based on awarding a per unit subsidy to qualified returned electronic products and ensuring a minimum producer collection volume while allowing larger collection volumes. Based on a real application from a Chinese electronics company that produces LCD TVs, our paper studies the optimal design of the product’s reverse supply chain when there is flexibility in settling the inspection locations of the returned products and flexibility in the volume of returned products collected. The problem is modeled as a nonlinear mixed-integer program and an efficient outer approximation-based solution approach is proposed. Analytical results and extensive numerical experiments based on this real application are conducted. Observations novel to the reverse logistics literature are related to the testing location decisions (upstream or downstream) and the optimal collection volumes of returned products. Particularly, we show how the government can stimulate the collection amount of returned products by increasing the unit subsidy and we also find that the company’s marginal benefit from improving the subsidy increases in a superlinear fashion. Furthermore, the highest collection volumes may not occur at the highest quality level of returned products for capacitated remanufacturers. The company can also be incentivized to increase the collection of returned products by permitting flexible testing locations. We also observe how the optimal testing locations vary for different levels of unit subsidy and different ratios of qualified and non-qualified returned products. Finally, conclusions and future research directions are provided.     

Selling with Money‐Back Guarantees: The Impact on Prices,Quantities, and Retail Profitability

In this paper, we consider a retailer adopting a “money‐back‐guaranteed” (MBG) sales policy, which allows customers to return products that do not meet their expectations to the retailer for a full or partial refund. The retailer either salvages returned products or resells them as open‐box items at a discount. We develop a model in which the retailer decides on the quantity to procure, the price for new products, the refund amount, as well as the price of returned products when they are sold as open‐box. Our model captures important features of MBG sales including demand uncertainty, consumer valuation uncertainty, consumer returns, the sale of returned products as open‐box items, and consumer choice between new and returned products and possibility of exchanges when restocking is considered. We show that selling with MBGs increases retail sales and profit. Furthermore, the second‐sale opportunity created by restocking returned products enables the retailer to generate additional revenues. Our analysis identifies the ideal conditions under which this practice is most beneficial to the retailer. Offering an MBG without restocking increases the new product price. We show that if the retailer decides to resell the returned items as open‐box, the price of the new product further increases, while open‐box items are sold at a discount. On the other hand, customers enjoy more generous refunds along with lower restocking fees. The opportunity to resell returned products also generally decreases the initial stocking levels of the retailer. Our extensive numerical study substantiates the analytical results and sharpens our insights into the drivers of performance of MBG policies and their impact on retail decisions.     

多油品供给受限下多油库被动配送车辆路径问题研究

成品油供给不足将导致加油站油品订单无法完全满足,如何安排有限油品的合理配送对保障能源供给安全至关重要。为此,本文考虑有限供给下不同客户配送的优先次序,开展配送计划、车辆调度和路径优化等油品配送网络规划活动,对多油品供给受限情况下多油库被动配送车辆路径问题（Multiple Depot Vehicle Routing Problem,MDVRP）进行深入研究。首先,文章构建了考虑需求优先等级和配送成本的多油品多油库车辆路径规划多目标优化模型。其次,采用多目标粒子群优化算法（Multi-Objective Particle Swarm Optimization,MOPSO）对模型进行求解,以实现车辆高效调度和油品配送路径优化。最后,基于CNPC在青岛市部分油库和加油站点的数据信息,构建油品配送网络进行实证检验。算例结果显示,配送车辆路径经过优化后,生成Pareto非劣解集,配送成本显著降低,配送满足率明显提高,这也进一步验证了该模型及相关算法的可行性和有效性。     

The Redevelopment of Bus Depots: A Transaction Cost Economic Analysis of a Change in the Use of Land in Hong Kong

This is a pioneering study on bus depots based on a review of the English-language literature on or related to them, which is motivated by the prevalence of real estate projects using the land of the former depots. The review is followed by some conjectures about the transaction cost advantages of bus depot sites as a source of development land and examines the hypothesis that redevelopment projects using former bus depots, compared to other uses, in Hong Kong are more easily approved under the statutory planning system. The literature review found that bus depots have attracted much academic attention, although research angles were conditioned by different social perceptions of bus depots. The empirical results of this case study did not reject the hypothesis. The limitations and implications of the study are discussed.     

Planning of a decentralized distribution network using bilevel optimization

This paper proposes a bilevel optimization problem to model the planning of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. Usually, the distribution network design problem decides on the opening of depots and the distribution from the depots to customers only and pays no attention to the manufacturing process itself. By way of example, the paper discusses the implications of formulating a bilevel model to integrate distribution and manufacturing, maintaining the hierarchy existing in the decision process. The resulting model is a bilevel mixed integer optimization problem. Hence, only small instances can be optimally solved in an acceptable computing time. In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.     

Optimal Price and Quantity of Refurbished Products

Many retail product returns can be refurbished and resold, typically at a reduced price. The price set for the refurbished products affects the demands for both new and refurbished products, while the refurbishment and resale activities incur costs. To maximize profit, a manufacturer in a competitive market must carefully choose the proportion of returned products to refurbish and their sale price. We model the sale, return, refurbishment, and resale processes in an open queueing network and formulate a mathematical program to find the optimal price and proportion to refurbish. Examination of the optimality conditions reveals the different situations in which it is optimal to refurbish none, some, or all of the returned products. Refurbishing operations may increase profit or may be required to relieve a manufacturing capacity bottleneck. A numerical study identifies characteristics of the new product market and refurbished products that encourage refurbishing and some situations in which small changes in the refurbishing cost and quality provoke large changes in the optimal policy.     

“线上销售/回收+线下服务”的闭环供应链定价与服务决策

对于“线上销售/回收+线下服务”的闭环供应链模式,研究了制造商在正向和逆向渠道中都与服务商进行收益共享情况下的最优销售/回收定价决策和最优服务水平决策,并比较了制造商领导的Stackelberg博弈、服务商领导的Stackelberg博弈、制造商与服务商Nash均衡博弈三种情形下的最优决策和最优利润。结果表明：最优的新产品销售价格和正向渠道服务水平均与正向渠道收益分成比例呈正相关;最优的废旧产品回收价格与逆向渠道收益分成比例呈负相关,而最优的逆向渠道服务水平与之呈正相关。制造商和服务商的最优利润不仅受正逆向渠道收益分成比例的影响,而且与新产品生产成本的大小有关：当新产品生产成本较小时,处于领导地位的一方获得的最优利润最大,而当新产品生产成本增大到一定程度后,对方处于领导地位时自身获得的最优利润反而最大,而双方均势时各自获得的最优利润均不占优。     

基于顾客战略行为下的供应链系统的绩效研究

供应链系统由一个供应商、一个零售商和顾客群组成,且顾客具有战略行为特征,其可以选择在一级市场上购买,也可以选择在二级市场上购买。在销售第一期,零售商向供应商提出订购,并在一级市场上销售,期末剩余产品被供应商回购;在销售第二期,供应商把回购产品通过直销渠道在二级市场上进行销售。采用参数分析和数值模拟得出,首先,顾客战略行为对供应链系统订购量、及系统总收益是否有负影响,取决于顾客对二级市场产品接受度。其次,分散管理系统中,通过提供依赖于集中管理系统下的最优订购量的回购合同,供应商能够协调分散管理系统;并且,无论是否存在顾客战略行为,分散管理系统中的最优回购价格均不受影响。最后,零售商是否接受回购合同,依赖于是否存在顾客战略行为,以及顾客对二级市场产品的接受度。     

Economic Lot Scheduling Problem with Returns

Motivated by a case study of a company that produces car parts, we study the multi‐product economic lot scheduling problem for a hybrid production line with manufacturing of new products and remanufacturing of returned products. For this economic lot scheduling problem with returns (ELSPR), we consider policies with a common cycle time for all products, and with one manufacturing lot and one remanufacturing lot for each product during a cycle. For a given cycle time, the problem is formulated as a mixed integer linear programming (MIP) problem, which provides the basis for an exact solution. The application of this model for one of the core products of the case study company indicates a 16% reduction in cost compared to the current lot scheduling policy.     

Consumer return policies in presence of a P2P market

Retailers selling products with valuation uncertainty often offer return policies to consumers to stimulate demand. However, some products that do not meet consumers’ expectations cannot be returned to the retailers either because of retailers’ strict restrictions on returns or because of short trial period. With the development of e-commerce, consumers who cannot return their products to retailers can resell them directly to others through electronic peer-to-peer (P2P) second-hand goods markets. This paper examines the effect of the presence of a P2P market on a retailer’s optimal return policy when the consumers are strategic and uncertain about their valuations. As a benchmark, we first examine the retailer’s optimal return policy when there is only a retailer-run resale market. Then, we analyze the retailer’s optimal return policy in presence of both the retailer-run resale market and the P2P market. Theoretical and numerical results show that, first, the presence of the P2P market is detrimental to the retailer in most cases. The presence of the P2P market is beneficial to the retailer only when the unit purchasing cost is very high, the consumers’ acceptance of products in the P2P market is relatively high and the transaction cost in the P2P market is relatively low; second, the consumer surplus is improved by the presence of P2P market; third, when the retailer-run resale market is the only second-hand products market, returned products are sold out; while in presence of the P2P market, the retailer will hold some inventory when the unit purchasing cost is very low; fourth, the selling price of new products is increased and the selling price of second-hand products in the retailer-run resale market is decreased with the emergence of the P2P market while the refund amount is increased in most cases.