随机需求下多供应商和多零售商的生产-库存-运输联合优化模型

考虑随机需求下多供应商和多零售商的生产-库存-运输联合优化问题.在联合优化时,首先利用最近邻算法将各零售商分成不同区域,分区后问题转化为随机需求下单供应商对多零售商的生产-库存-运输联合优化问题.在每个分区内,由供应商统一决策其分区内各零售商的送货量和送货时间.利用粒子群算法和模拟退火算法相结合的两阶段算法求出最优送货量、最优运输路径和最大期望总利润.然后采用收入共享契约将增加的利润合理分配给各供应商和各零售商,使各方利润都得到增加,从而促使各方愿意合作.通过数值算例验证了联合优化模型优于独立决策模型.     

供应链多层规划问题及其合作对策协商求解

针对由制造商、分销中心和零售商组成的多级分布式供应链协同计划问题,建立了三层规划生产-分销计划谈判模型,设计了基于合作对策的两步协商方法。首先,基于模糊隶属度原理,将三层规划问题转化为单层规划问题。接着,设计了基于合作对策的两步协商过程,描述了两步协商模型和交互协商算法步骤,并对算法进行了性能分析。最后,给出了基于多层规划的协同生产-分销计划模型,并得到了基于合作对策的协商算法的解决方案。并通过与其它优化策略的对比,验证该解决方案的优越性。     

随机需求下单供应商与多零售商的生产—库存—运输联合优化模型

考虑随机需求下单供应商和多零售商的生产-库存-运输联合优化问题.在独立决策时,各零售商独立决策其最优订货量和最优订货点,供应商根据各零售商的决策来为之配送.在联合决策时,由供应商统一决策各零售商的送货量和送货时间,并基于此建立单供应商与多零售商的生产-库存-运输优化模型,利用粒子群算法和模拟退火算法相结合的两阶段算法求出最优送货量、最优运输路径和最大期望总利润.然后采用收入共享契约将增加的利润合理分配给供应商和各零售商,使各方利润都得到增加,从而促使各方愿意合作.最后,通过数值算例验证了联合优化模型优于独立决策模型.     

蔬果类商品网上直销包装作业工序优化模型研究

针对蔬果类商品网上直销模式下,其标准销售单元包装作业问题规模大、商品品类多、订单个性化强、生产配送周期多等特点,基于批量流水作业生产、JIT准时制生产及周期调度的思想,研究该类商品标准销售单元包装作业的生产调度问题,建立蔬果类商品网上直销包装作业优化模型,并设计改进的“模拟增压——退火算法”对其进行求解,以便制定出合理的包装作业计划,有效衔接采摘和订单分拣作业以及后续装车作业,缩短包装时间,保证蔬菜的新鲜性。最后,通过应用实例验证模型和算法的有效性,结果表明,本文周期调度方法得到的调度方案比一般的非周期调度方法大大节约了包装作业成本,为蔬果类商品网上直销企业生成包装作业计划提供了理论指导。     

基于动态遗传算法的共享配送模式研究

针对传统配送中配送车辆装载率低、车辆数量多及配送成本高等问题,提出不同类型零售商资源共享的城市配送优化方法,并考虑配送中的车辆油耗与不确定需求等问题。以总配送成本最低为目标建立模型,利用基于动态参数的改进遗传算法对模型进行求解。最后,通过算例对共享配送模式与算法进行测试。结果表明,共享配送模式能够有效减低车辆数量、提高装载率及降低配送成本,同时改进遗传算法能够高效、准确对模型求解。     

企业社会责任下碳减排优化策略与协调机制研究

基于企业社会责任(CSR)的视角,本文研究由生产低碳产品的制造商和零售商组成的二级供应链的最优策略及供应链协调问题。通过构造供应链成员具有社会责任感的效用函数,分析了CSR对各成员的利润和环境的影响。研究发现:制造商和零售商都是通过降低碳排放水平来体现社会责任感;无论制造商有社会责任感还是零售商有社会责任感,供应链的利润都增大;在收益共享-成本分摊合同(RC合同)下协调,可以使制造商和零售商实现双赢(帕累托最优);零售商应该承担更多的社会责任,降低碳排放水平。     

基于前摄性调度的电动汽车路径问题研究

针对车辆调度过程中资源不均衡的问题,利用需求的不确定性,将配送周期划分为初始配送阶段和补货阶段,建立多阶段电动汽车的两级车辆路径优化模型.根据需求的动态程度对配送区域进行划分,结合前摄性调度和反应性调度策略,提出了一种混合禁忌搜索算法(HTSA)来求解该模型.在真实的案例和多个基准评估算例上的实验结果表明:模型和算法的性能优于传统的启发式算法,具有一定的实用价值.     

一种基于双链量子编码的动态车辆路径问题解决策略

针对配送调度事件动态变化的动态车辆路径问题(DVRP), 以最小化运输成本、最小化配送时间 与最大化载货率为目标, 建立了问题的数学模型,提出了改进的多相量子粒子群算法. 针对DVRP问题的特点,提出基于车辆链和货物链的双链量子编码方法; 同时设计了基于周期和 重调度因子驱动的动态调度策略. 最后将方法应用于动态仿真算例, 并与其他经典算法比较, 结果验证了所提出方法的有效性.     

成品油配送多车舱车辆指派及路径优化问题研究

针对成品油配送中多车型、多车舱的车辆优化调度难题,综合考虑多车型车辆指派、多车舱车辆装载及路径安排等决策,以派车成本与油耗成本之和的总成本最小为目标,建立了多车型多车舱的车辆优化调度模型。为降低模型求解的复杂性,本文提出一种基于C-W节约算法的“需求拆分→合并装载”的车辆装载策略,并综合利用Relocate和Exchange算子进行并行邻域搜索改进,获得优化的成品油配送方案。最后,通过算例验证了本文提出的模型与算法用于求解大规模成品油配送问题的有效性。并通过数据实验揭示了以下规律:1)多车舱车辆相对于单车舱车辆在运营成本上具有优越性;2)大型车辆适合远距离配送,小型车辆适合近距离配送;3)多车型车辆混合配送相对于单车型车辆配送在运营成本上具有优越性。这些规律可为成品油配送公司的车辆配置提供决策参考。     

基于改进模拟退火算法的推动式生产-配送协调优化

为减小物资生产与配送不协调造成的成本及生产资源浪费,建立了考虑推动式生产调度的物资配送优化模型,并针对标准模拟退火算法受随机因素影响易陷入局部最优的缺点,设计带有回火与缓冷操作的改进模拟退火算法对模型求解,确定了优化的车辆配送路线以及物资生产计划。对比实验结果表明:相对于单纯的物资配送优化模型,考虑推动式生产调度的配送优化模型,能够有效减小物资滞留时间以及配送延误成本;相较于标准模拟退火算法,改进算法搜索到了更优解,且计算结果的标准差减小了93.42%,稳定性更好;同时,改进模拟退火算法具有较低的偏差率,在中小规模算例中求解质量较高,平均偏差率在0.5%以内。     

Nash game model for optimizing market strategies,configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

This paper discusses how a manufacturer and its retailers interact with each other to optimize their product marketing strategies, platform product configuration and inventory policies in a VMI (Vendor Managed Inventory) supply chain. The manufacturer procures raw materials from multiple suppliers to produce a family of products sold to multiple retailers. Multiple types of products are substitutable each other to end customers. The manufacturer makes its decision on raw materials’ procurement, platform product configuration, product replenishment policies to retailers with VMI, price discount rate, and advertising investment to maximize its profit. Retailers in turn consider the optimal local advertising investments and retail prices to maximize their profits. This problem is modeled as a dual simultaneous non-cooperative game (as a dual Nash game) model with two sub-games. One is between the retailers serving in competing retail markets and the other is between the manufacturer and the retailers. This paper combines analytical, iterative and GA (genetic algorithm) methods to develop a game solution algorithm to find the Nash equilibrium. A numerical example is conducted to test the proposed model and algorithm, and gain managerial implications.     

基于最优让步均衡协调策略的供应链差价补偿机制研究

制造商为了激励零售商订购更多数量的产品,会在产品零售价下调时提供给零售商一定的补偿,如何制定最优补偿机制是提高供应链收益的关键问题。为此,建立了两阶段销售差价补偿机制下制造商与零售商的博弈模型,分析了纳什均衡解和Stackelberg均衡解下制造商对零售商的差价补偿机制的决策行为,导出了在最优让步均衡策略下差价补偿机制定量关系,并提出了求解给定差价补偿系数下的近似最优让步均衡策略的算法。通过智能产品算例的分析,表明差价补偿机制能提高供应链的期望收益,增加零售商的订购量,进一步,说明差价补偿机制可以有效地改善零供关系。     

Product variety, pricing and differentiation in a supply chain

Manufacturers typically sell consumer products through retailers and the presence of intermediaries has interesting ramifications for their product variety and pricing decisions. Retailers may want higher variety to help reduce price competition but the costs of variety are borne by the manufacturer. The increased variety may increase demand and profits for the manufacturer too but this depends on market-specific factors as well as costs. We explore these interactions through a model wherein a manufacturer sells multiple product variants at a wholesale price to two retailers who in turn compete for consumers. Consumers choose between the retailers based on the price and variety offered by each retailer and the search or transportation cost incurred by the consumer, equivalent to the level of retailer differentiation in our model. Several insights emerge from the analysis. The manufacturer offers the same variety to both retailers and this variety increases with market size and consumer sensitivity to variety. We find that some retailer differentiation benefits the retailers (not the manufacturer) but too much differentiation hurts both the retailers and the manufacturer. If the market is fully covered, then the channel is coordinated even with a simple wholesale pricing contract. If the retailers incur costs to sell the product, the manufacturer surprisingly loses out more than the retailers and in fact absorbs some or all of the retailer costs. Finally, asymmetry between retailers has some unexpected consequences. For example, variety is not impacted by asymmetry in consumer preferences for a retailer and the manufacturer offers the same variety to both retailers.     

Price competition and store competition: Store brands vs. national brand

This paper studies pricing strategies in a market channel composed of one national brand manufacturer and two retailers who, each, carry their own store brand and a national brand products. The model accounts for product competition between store brands and the national brand products, as well as for store competition between retailers.     

Manufacturer’s revenue-sharing contract and retail competition

This paper investigates a revenue-sharing contract for coordinating a supply chain comprising one manufacturer and two competing retailers. The manufacturer, as a Stackelberg leader, offers a revenue-sharing contract to two competing retailers who face stochastic demand before the selling season. Under the offered contract terms, the competing retailers are to determine the quantities to be ordered from the manufacturer, prior to the season, and the retail price at which to sell the items during the season. The process of pricing and ordering is expected to result in an equilibrium as in the Bayesian Nash game. On the basis of anticipated responses and actions of the retailers, the manufacturer designs the revenue-sharing contract. Adopting the classic newsvendor problem model framework and using numerical methods, the study finds that the provision of revenue-sharing in the contract can obtain better performance than a price-only contract. However, the benefits earned under the revenue-sharing contract by different supply chain partners differ because of the impact of demand variability and price-sensitivity factors. The paper also analyses the impact of demand variability on decisions about optimal retail price, order quantity and profit sharing between the manufacturer and the retailers. Lastly, it investigates how the competition (between retailers) factor influences the decision-making of supply chain members in response to uncertain demand and profit variability.     

Trade credit competition between two retailers in a supply chain under credit-linked retail price and market demand

The paper considers a supply chain system in which the sole manufacturer supplies the same product to two retailers who compete in offering trade credit period to customers. Both the market demand and retail prices vary with the trade credit periods offered by the retailers. The manufacturer also provides a trade credit period to both the retailers to settle down their accounts. The net profit function of the supply chain is derived considering possible relationships among the trade credit periods offered by the manufacturer and the retailers and the time when each retailer receives the last payment from his customer. An algorithm is developed to find the optimal solution of the proposed model. From the numerical study, it is observed that a two-level trade credit financing can increase profits not only for the manufacturer and the retailers but also for the whole supply chain.     

由零售商负责回收的多期闭环供应链网络均衡

本文研究了零售商回收模式下多期闭环供应链网络均衡问题。制造商通过零售渠道将产品销售给消费者,以满足消费市场需求,同时消费产生的废旧品由零售商回收返回制造商处进行再制造,通过产品库存和回收废旧品连接相邻规划期。运用变分不等式理论和互补理论,分别刻画了制造市场、零售市场和消费市场的均衡,接着构建了多期闭环供应链网络均衡模型。利用变分不等式的投影收缩算法,对模型进行求解。算例着重分析了废旧品利用率对网络均衡状态和供应链成员利润的影响。结果表明:当制造商的废旧品利用率逐渐增加时,回收量逐渐增加,制造商的利润先减后增,零售商利润一直增加,而供应链总利润一直增加,供应链网络中的最优决策变量主要受到回收量约束的影响。     

Optimal selection of retailers for a manufacturing vendor in a vendor managed inventory system

A Vendor Managed Inventory (VMI) system consists of a manufacturing vendor and a number of retailers. In such a system, it is essential for the vendor to optimally determine retailer selection and other related decisions, such as the product’s replenishment cycle time and the wholesale price, in order to maximize his profit. Meanwhile, each retailer’s decisions on her willingness to enter the system and retail price are simultaneously considered in the retailer selection process. However, the above interactive decision making is complex and the available studies on interactive retailer selection are scarce. In this study, we formulate the retailer selection problem as a Stackelberg game model to help the manufacturer, as a vendor, optimally select his retailers to form a VMI system. This model is non-linear, mixed-integer, game-theoretic, and analytically intractable. Therefore, we further develop a hybrid algorithm for effectively and efficiently solving the developed model. The hybrid algorithm combines dynamic programming (DP), genetic algorithm (GA) and analytical methods. As demonstrated by our numerical studies, the optimal retailer selection can increase the manufacturer’s profit by up to 90% and the selected retailers’ profits significantly compared to non-selection strategy. The proposed hybrid algorithm can solve the model within a minute for a problem with 100 candidate retailers, whereas a pure GA has to take more than 1 h to solve a small sized problem of 20 candidate retailers achieving an objective value no worse than that obtained by the hybrid algorithm.     

A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem

Integrated production–distribution planning is one of the most important issues in supply chain management (SCM). We consider a supply chain (SC) network to consist of a manufacturer, with multiple plants, products, distribution centers (DCs), retailers and customers. A multi-objective linear programming problem for integrating production–distribution, which considers various simultaneously conflicting objectives, is developed. The decision maker’s imprecise aspiration levels of goals are incorporated into the model using a fuzzy goal programming approach. Due to complexity of the considered problem we propose three meta-heuristics to tackle the problem. A simple genetic algorithm and a particle swarm optimization (PSO) algorithm with a new fitness function, and an improved hybrid genetic algorithm are developed. In order to show the efficiency of the proposed methods, two classes of problems are considered and their instances are solved using all methods. The obtained results show that the improved hybrid genetic algorithm gives us the best solutions in a reasonable computational time.     

转包且具有不同费用时间段的排序问题

本文研究制造商可以将工件转包给承包商加工的排序模型,承包商仅有一台机器,转包费用由分配给转包工件的不同时间段费用确定.本文分别研究制造商有一台单机及两台自由作业机器环境情形,需要确定被转包工件集及全部工件的加工顺序,使得工件最大完工时间与转包费用和最小.本文利用归约方法对制造商每个机器环境,证明问题NP困难性,并提出动态规划算法.