A Simulation Study of Dynamic Order-up-to Policies in a Supply Chain with Non-Stationary Customer Demand and Information Sharing

This study deals with the development of heuristic settings for dynamic order-up-to levels at different installations in a supply chain with non-stationary customer demand, in order to minimize the sum of inventory, shortage and transport costs. Balance equations are developed to capture the dynamics of supply chain. Mathematical expressions are derived to determine the dynamic order-up-to levels as a function of forecasted demand, forecasted replenishment leadtime and safety factor. Towards this attempt, different heuristic settings with respect to the safety factor are first proposed. Next, three levels of information sharing among the members of the supply chain are considered to study the impact of information sharing on the total cost. Finally, the use of a forecasting technique for predicting the replenishment leadtime is considered. A supply chain is simulated to evaluate the proposed dynamic order-up-to policies based on various heuristic settings. It is found that the use of forecast of replenishment leadtime and customer demand information sharing, and the proposed safety-stock heuristic settings in the determination of dynamic order-up-to levels, significantly reduce the sum of discounted inventory, shortage and transport costs of the supply chain.     

Synchronization in multi-echelon supply chain applying timing discount

Due to the increasing emphasis on the effective management of the supply chain, synchronization and cooperation issues between suppliers and retailers in decentralized multi-echelon inventory/distribution systems have gained much attention in the recent years. In this paper, we consider coordination issues of a distribution system composed of a manufacturer, a supplier (distributor), and several retailers. The supplier outsourcing a third party offers a timing discount to multiple retailers in order to synchronize the timing of their orders with the order cycle. It is also assumed that retailers are allowed to face stock outs. In this paper, a mathematical model is developed to analyze the problem. Results show that while synchronizing the supplier and the outsourcer enhances the supply chain efficiency, offering any type of timing discount by the supplier decreases the supply chain efficiency. It is also noted that having coordination between the manufacturer and the supplier has no impact on the supplier’s profit but may decrease the retailer’s costs. It is believed that our findings provide potential and significant managerial implications in the area of supply chain coordination when these systems are decentralized.     

基于三前馈APIOBPCS的供应链弹性与运作成本评估

为兼顾供应链系统的弹性和运作成本,提出三前馈自动渠道的、基于库存和定购的生产控制系统(Triple feed-forward automatic pipeline, inventory and order-based production control system, TFF-APIOBPCS)。在自动渠道的、基于库存和定购的生产控制系统模型中,增加一阶微分前馈环节,以部分抵消需求波动对库存的影响。在零稳态误差情况下针对生产控制系统的不同极点分布,分析一阶微分前馈环节的参数与供应链弹性的关系。综合考虑库存成本及生产调节成本,构造供应链系统的运作成本模型。通过阶跃需求、随机需求下的供应链系统仿真,评估一阶前馈环节参数对供应链弹性及运作成本的影响,验证三前馈自动渠道的、基于库存和定购的生产控制系统的有效性。结果表明,针对不同波动程度的需求,合理设置一阶微分前馈环节的参数,可以获得弹性与运作成本的良好均衡。     

Inventory replenishment and delivery planning in a two-level supply chain with compound Poisson demands

This paper presents a model for integrating inventory replenishment and delivery planning in a two-level supply chain consisting of a supplier and a retailer. The supplier is authorized to manage the inventory level of the retailer by using the information on demands from final customers and the inventory level of the retailer. The problem considered here is to determine order-up-to levels of the supplier and the retailer simultaneously for the objective of minimizing the expected long-run average cost, which is composed of replenishment cost at the supplier, delivery cost to the retailer, and inventory holding costs at both members. We develop a renewal theoretic optimization model for a case of compound Poisson demands with distribution-free order quantities and present an approximation method for obtaining a solution of the problem. In addition, a closed-form solution is derived for the problem with a special case of compound Poisson demands, in which demand quantities follow an exponential distribution. A series of simulation tests show that the solutions obtained from the approximated cost functions are reasonably good.     

Modeling and solving a one-supplier multi-vehicle production-inventory-distribution problem with clustered retailers

This paper considers a supply chain management problem which integrates production, inventory, and distribution decisions. The supply chain is composed of one supplier production facility and several retailers located in a given geographic region. The supplier is responsible for the production and the replenishment of the inventory of retailers, in a vendor managed inventory (VMI) context. The distance between retailers is negligible compared to the distance between the supplier and the retailers’ region. Thus, for each vehicle, there is a major fixed cost for traveling to the cluster of retailers and a minor fixed cost for visiting each individual retailer. The problem consists of determining quantities to be produced, quantities to be delivered to retailers, vehicles to be used, and retailers to be serviced by each vehicle. This problem is an extension of the one warehouse multi-retailer problem with the consideration of production planning and storage and vehicle capacity limitations in addition to fixed vehicle utilization costs and retailer servicing costs. The objective is to minimize a total cost composed of production, transportation, and inventory holding costs at the supplier and at the retailers. Two mixed integer linear programming formulations are proposed and six families of valid inequalities are added to strengthen these formulations. Two of these families are new and the others are adapted from the literature. The numerical results show that the valid inequalities considerably improve the quality of the formulations. Moreover, the parameters that influence the most computational times are analyzed.     

Capacities-based supply chain network design considering demand uncertainty using two-stage stochastic programming

The design of a supply chain (SC) aims to minimize cost so the product can reach the customer at the cheapest cost with flexible demand. The demand of a product is variable with time and environment. Most of the researchers have considered investment cost, processing cost, and transportation cost as variable costs to minimize the cost while considering a constant demand. In actual practice, the demands are flexible. In this paper, a two-stage stochastic programming model has been proposed for a capacities-based network design of a supply chain for flexible demands while considering inventory carrying cost and missed opportunity cost in addition to the above-mentioned costs. It will enhance the logistic planning and seek the location network optimally. Furthermore, in the first stage, decision variables represent different nodes (facility locations of echelons) of the supply chain, with the assumption that they will be considered at the design stage before uncertain parameters are unveiled. On the other hand, decision variables related to the amount of products to be produced and stored in the nodes of the SC, the flows of materials among the entities of the network, and shortfalls and excess at the customer centers are considered as second-stage variables. The methodology has been illustrated by solving an example. It was found that the proposed model yields more feasible and advantageous results.     

基于APIOBPCS的供应链生产控制方法

为了均衡生产更改成本和库存成本,研究了自动库存反馈补偿的订单型生产控制方法,提出基于此方法的供应链生产控制模型,建立控制模型的生产更改成本和系统库存成本的数学表达式,并在此基础上建立均衡供应链生产更改成本和库存成本的优化模型。分析控制模型的参数设置对供应链系统成本性能的影响,并用实例验证模型的科学性和实用性。     

Hybrid approach to distribution planning reflecting a stochastic supply chain

Today’s business environment is experiencing as a period of expansion and the globalization. Therefore, a distribution plan with low cost and high customer satisfaction in supply chain management (SCM) has been widely investigated. The purpose of this study is to establish optimal distribution planning in the supply chain. In this paper, a hybrid approach involving a genetic algorithm (GA) and simulation is presented to solve this problem. The GA is employed in order to quickly generate feasible distribution sequences. Considering uncertain factors such as queuing, breakdowns and repairing time in the supply chain, the simulation is used to minimize completion time for the distribution plan. The computational results for an example of a simple supply chain are given and discussed to validate the proposed approach. We obtained a more realistic distribution plan with optimal completion time by performing the iterative hybrid GA simulation procedure which reflects the stochastic nature of supply chains.     

基于协同进化粒子群的多层供应链协同优化

为了从整体角度优化调度供应链网络的各个环节,研究了带软时间窗的分批配送问题及其对需求分配与生产调度的影响,考虑在满足一定客户满意度水平条件下的最小化运作成本。建立了该问题的模型,针对此模型设计了协同进化粒子群优化算法并进行求解。通过实验研究表明,软时间窗对于问题的运作成本有很大的影响,整个供应链网络的协同优化对降低运作成本起到了关键的作用。     

双分销渠道下短生命周期产品供应链转运策略

为解决双分渠道供应链中供需不匹配的问题,研究了制造商生产能力约束下双分渠道的短生命周期产品供应链库存协作问题,分析了非合作情况下的供应链订货决策、转运策略下的供应链订货决策,以及需求服从正态分布条件下的订货决策,并对不同情形下的订货决策行为进行了相应的数值分析,提出了采用转运策略来减少短生命周期产品供需不匹配的现象。研究结果表明,转运策略可以增强供应链供需匹配性,当市场需求不确定性不断变大时,能更好地缓冲市场波动风险,并增加供应链的期望利润。另外,当存在制造商生产能力约束时,转运策略能够获得比非合作策略更高的供应链服务水平。     

基于ASP平台的供应链协同运作模式研究

激烈的市场竞争环境给供应链管理模式下的制造企业提出了新的发展要求,供应链协同是改进消费者服务,减少库存,减少供应链成本,提升竞争力,提高消费者忠诚度的一条途径.为了实现供应链协同运作的目的,需要在跨平台、跨应用方面达成协同并实现协同管理.通过研究开发网络化制造环境下供应链协同的企业动态联盟运作模式,建立基于应用服务供应商(ASP)的供应链协同运作平台,实现集成企业中采购、库存生产计划等业务过程的管理协同和信息协同,增强对市场需求不确定性的快速反应能力,提高供应链的整体竞争力.     

Supply chain focus dependent safety stock placement

Increasing globalization, growing product range diversity, and rising consumer awareness are making markets highly competitive, forcing supply chains to adapt constantly to different stimuli. Growing competition between supply chains (as well as players within them) is also warranting a priority for overall supply chain performance over the goals of individual players. It is now well established in the literature that, among the many order winners, both overall supply chain cost and responsiveness (i.e., supply chain lead time) are the most significant determinants of supply chain competitiveness. The literature, however, mostly focuses on supply chain cost minimization with rather simplistic treatment of responsiveness. By introducing the concept of a coefficient of inverse responsiveness (CIR), we facilitate efficient introduction of responsiveness related costs into the scheme of supply chain (SC) performance evaluation and/or optimization. Thus, our model aids supply chain managers in achieving better strategic fit between individual business unit strategies and overall supply chain requirements in terms of cost efficiency and responsiveness. In particular, it aids in strategic placement of safety stocks at different stages in the supply chain. Our model also offers managerial insights that help improve our intuitions into supply chain dynamics. The model is more suited for strategic SC alignment, for example, when dealing with product changeovers or introduction of new product, rather than for operational control.     

Optimization of total inventory cost and order fill rate in a supply chain using PSO

This paper proposes a method to optimize both the total cost and order fill rates in a supply chain using the particle swarm optimization (PSO) method. This method automatically adjusts the initial inventory levels of all tiers involved in a supply chain by considering information quality level (IQL), which is determined by the degree of availability of lead time history data. Analyses of variance are used to examine if there are any effects of IQL on the total cost and order fill rates. The results show that the proposed method finds better solutions which provide a lower inventory level while maintaining higher order fill rates than when PSO is not applied.     

A particle swarm optimization approach for constraint joint single buyer-single vendor inventory problem with changeable lead time and (r,Q) policy in supply chain

In this paper, the chance-constraint joint single vendor-single buyer inventory problem is considered in which the demand is stochastic and the lead time is assumed to vary linearly with respect to the lot size. The shortage in combination of back order and lost sale is considered and the demand follows a uniform distribution. The order should be placed in multiple of packets, the service rate limitation on each product is considered a chance constraint, and there is a limited budget for the buyer to purchase the products. The goal is to determine the re-order point and the order quantity of each product such that the chain total cost is minimized. The model of this problem is shown to be an integer nonlinear programming type and in order to solve it, a particle swarm optimization (PSO) approach is used. To assess the efficiency of the proposed algorithm, the model is solved using both genetic algorithm and simulated annealing approaches as well. The results of the comparisons by a numerical example, in which a sensitivity analysis on the model parameters is also performed, show that the proposed PSO algorithm performs better than the other two methods in terms of the total supply chain costs.     

Bi-objective heuristics for multi-item freights distribution planning problem in crossdocking networks

Crossdocking is a distribution strategy in which distribution centers operate as transfer points to harmonize the continuous physical flow through supply chain with the least storage. The coordination of this system in a network of crossdocks with multitype and time-restricted pickups and deliveries requires a complex planning. This paper addresses the distribution planning problem of crossdocking network, considering transshipment possibility among crossdocks and tardiness permission for some pickups. The problem is formulated as a bi-objective integer-programming model minimizing total transportation and holding costs and total tardiness. An innovative heuristic procedure to construct an effective initial solution and three improving algorithms based on appropriate meta-heuristics (variable neighborhood search, tabu search, and simulated annealing) is developed to solve the problem. Experimental results demonstrate the potency of proposed algorithms achieving remarkable results.     

大规模定制下制造商延迟生产的成本优化模型

为解决大规模定制下延迟生产系统中制造商的生产成本优化问题,建立了大规模定制下制造商实施延迟生产的生产成本优化基本模型和扩展模型,以大规模定制下延迟生产系统的生产成本最小化为目标,综合考虑了固定资产的投资成本、制造成本、在制品持有成本、半成品库存成本,以及客户提前期问题.分析了客户订单分离点最佳位置及其决定因素,并指出了客户需求平均到达率、定制化产品种类数量,以及制造中心平均生产率对客户订单分离点最佳位置的影响.最后,对延迟生产系统的生产成本优化模型进行了仿真.     

Simulation modeling for comparative evaluation of supply chain management strategies

Supply chain management (SCM) has become one of the most important strategies for achieving competitive advantage in different industries in the last decade. Researchers have investigated various processes in the planning and development of supply chains. However, increasing attention has been placed on performance, design and analysis of supply chain models. A supply chain is a complex model that is very difficult to analyze, in particular, with respect to performance. Simulation is one of the effective tools to evaluate the control mechanism for a supply chain. In this paper, five common supply chain models have been built and tested with the aid of simulation. Various performance measures such as transportation cost, resources utilization, inventory level, and order cycle time will be calculated for comparative indications. The methodology that is presented in this paper can be extended to any real life applications in SCM.     

基于CPFR的供应链体系结构和运作研究

合作计划、预测与补给是近年来出现的一种面向供应链的新型合作伙伴关系策略 ,对于供应链伙伴改善合作关系、提高预测准确度和供应链效率、减少库存、提高消费者满意程度等均有重要的意义。本文阐述了合作计划、预测与补给的概念和特点 ,提出了基于合作计划、预测与补给的供应链体系结构和合作关系 ,分析和论述了其运作过程 ,建立了合作企业价值观     

A two-echelon inventory model with product returns considering demands dependent return rates

Supply chains usually deal with processing of returned products so that part of the customer demands can be met using the remanufactured products. Therefore, to have an effective inventory management system, it is necessary to consider the effects of the returned products on inventory policy of all involved parties in a supply chain. In this paper, a two-echelon inventory model is developed for a single reusable product in which the return rates explicitly depend on demand streams. The remanufacturing process transforms a returned product to a serviceable one. We extend the basic inventory model incorporating both manufacturing and remanufacturing processes using a continuous review inventory policy. We apply a dynamic programming approach for solving our extended model. To show the applicability of the model, a numerical example is presented. Sensitivity analysis results of the model are consistent with the expected behaviors of our developed model.     

Developing a two-echelon mathematical model for a vendor-managed inventory (VMI) system

Vendor-managed inventory (VMI) system is a mechanism where the supplier creates the purchase orders based on the demand information exchanged by the retailer/customer. In this paper, the performance of the traditional and VMI system is compared. Mathematical modeling is applied and total inventory cost in the supply chain is used as the performance measure. The supply chain is considered in two levels, i.e., buyer and supplier, with the assumption that the supplier faces only one buyer as the contract party. Since none of the previous works quantitatively directed the practitioners to select the traditional or VMI system, the extent point is introduced in which the difference in total cost of both systems is minimal. It is applied to investigate how increasing or reducing the related parameters changes total cost of two systems with respect to each other. A numerical example and sensitivity analysis are provided to illustrate the theory and derive the extent points and percentage of difference in total cost of the traditional and VMI system. The results show that VMI works better and delivers lower cost in all conditions including back order, and as one goes farther from the extent point, the application of VMI is more justified.