Lead Time Uncertainty Research Articles

Day-Definite Full Container Load Service for Time-Sensitive Shippers

The authors quantify the benefits of a newly introduced logistics product, day-definite Full Container-load (FCL), in terms of its cost reduction relative to other existing products – regular FCL and airfreight, from the perspective of a logistic manager in an intercontinental supply chain facing lead-time uncertainties. Numerical examples and sensitivity analysis are provided to illustrate the comparison across the above-mentioned three logistics products and the impact of other factors on the performance of these logistics products.

Impact of transportation lead-time variability on the economic and environmental performance of inventory systems

Storage and transportation of goods within global supply chains is a major cause of environmental damage in modern value added processes. Thus, in the past, theory and practice developed several approaches in order to decrease these negative environmental impacts that frequently counteract the traditional efficiency-oriented ambitions. However, in many cases the economic and environmental performance can be improved at the same time. As many activities in logistics and inventory management are related to the treatment of potential uncertainties in the system by establishing redundancies, the reduction of uncertainty has equally a positive impact on both performance measures. To investigate the interrelation between uncertainty and the economic and environmental performance of supply chains, a serial inventory system consisting of a manufacturer who works with overseas suppliers and a carrier is considered, whereas the carrier is able to reduce lead time uncertainty. The relationships between uncertainties and the economic and environmental performance of the considered inventory system are highlighted by a simulation study based on empirical data from an international container shipping supply chain.

Post-seismic supply chain risk management: A system dynamics disruption analysis approach for inventory and logistics planning

Post-seismic inventory and logistics planning under incomplete and fuzzy information is an important yet understudied area in supply chain risk management. The goal of this paper is to propose a system dynamics model to analyze the behaviors of disrupted disaster relief supply chain by simulating the uncertainties associated with predicting post-seismic road network and delayed information. The simulation results indicate: (1) information delay has different influences over the relief head-quarter (the upstream) and the disaster-affected areas (the downstream); and (2) the change of road conditions and shipment schedules have impact on the on-time transportation rate in supply chain management. Furthermore, this paper defined and tested supplies' replenishment solutions combined with three inventory planning strategies and four forecasting methods under different lead time uncertainties. The results show that: (1) a strategy that considers information from both the post-seismic management center and the affected areas can provide a better logistic plan than an one takes information from one side; (2) the smooth-the-trend forecasting method is suitable for inventory and logistic planning when the post-seismic situations are volatile, while the quick-response forecasting method has good performance in stable environments. In addition, this paper proposes decision tree to help decision makers choose the appropriate stocking strategies.

Supply planning and inventory control under lead time uncertainty: A review

In literature, most papers examine several stochastic demand processes where order lead times are constant. In reality, lead time is rarely constant; unpredictable events in the supply system cause unpredictable delays. It is true that in certain special cases, lead time uncertainty has essentially no effect and can be ignored. Nevertheless more often, lead time fluctuations strongly degrade performance, just as demand uncertainty does. Seemingly, lead time uncertainty has been neglected for a long time in favor of studying demand uncertainties. Industry agrees that it is overdue and there is a need to rectify this oversight. Nowadays, this gap in research activity begins to be filled in order to respond to companies having non-deterministic lead-times constraints. This paper reviews some of existing literature of supply planning under uncertainty of lead times. The extensive literature review that we compiled consists of citations from 1970 to 2012. A classification scheme for supply planning under uncertainty is defined.

Integration of additional purchase cost to reduce the lead time uncertainty for one level assembly system

We consider the supply planning for one level assembly system under uncertainty of lead times. The finished product need several components for the assembly operation. The lead times can be uncertain for different reasons such as machine breakdowns, transport delay, strike, etc. In literature, this type of problem was studied in the case of random lead times that follow continuous distributions as well as in the case of any discrete laws with known distribution. We consider the case of discrete distributions to be closer to the industrial reality because often in real life situations the lead time is expressed as the number of periods. Typically, this is an inventory control problem where the objective is to minimize the component holding and backlog costs for the finished product due to the uncertainty of lead times. Indeed, as the finished product is assembled by using several types of components, the assembly is stopped even if a single type of component is delayed. The other components are stored between their arrival and the arrival of the latest component. To reduce stock and backlog costs, we propose to pay the supplier more, if he/she agrees to decrease his lead time uncertainty. A model describing this choice is suggested.

Positioning a Decoupling Point in a Semiconductor Supply Chain under Demand and Lead Time Uncertainty

Most of high-tech industries are facing unpredictable demand, short product lifecycles, and globally-spreading logistics. To surmount such a challenging environment, semiconductor industry practices have found the “push-pull strategy”, which is a hybrid approach of make-to-stock and make-to-order, as an effective solution. The position of a “decoupling point”, which is the boundary between make-to-stock and make-to-order, is one of the critical elements that influence a successful implementation of the push-pull strategy. This research addresses this issue by investigating the positioning of a decoupling point in a semiconductor supply chain based on the qualitative framework and simulation analysis. Several guidelines on how the decoupling point should be positioned under demand and lead time uncertainty are presented.

Optimised asset replacement strategy in the presence of lead time uncertainty

Abstract This paper develops an optimal replacement strategy for capital intensive equipment with long delivery lead time. The strategy is based on an extended version of the real options approach to repeated replacement decisions, in which the goal is to determine the operating cost and delivery lead-time conditions upon which a replacement should be ordered. The real options approach to capital replacement problems is superior to traditional net present value (NPV) approaches, as it values of the option to adapt decisions based on current (rather than predicted) system conditions. However, previous applications of the real options approach to repeated replacement have not considered the impact of long and uncertain lead times, and have therefore focused on when to replace rather than when to order. Delivery lead times are an important consideration in an expanding mining sector in which demand for heavy mobile equipment (HME) exceeds the capacity of suppliers to provide the equipment in a timely manner. The inclusion of a lead time element results in a decision with an “option” period and an “option-less” period. Simulations are used to demonstrate the improved outcome of real options based replacement strategies compared with those derived using a traditional NPV approach, both with and without lead times. Further the performance of the order placement strategy with different boundary conditions, bounded and reflecting, is explored. No appreciable difference in performance of these strategies was identified. The optimal order placement strategy incorporating delivery lead times is displayed on a simple chart which is accessible to fleet management personnel.

A Minimum Variance Control Theory Perspective on Supply Chain Lead Time Uncertainty

This paper addresses the lead time uncertainty problem in supply chain systems. In our previous paper [Xu et al. Ind. Eng. Chem. Res.2010,49,8644], we have investigated the impact of demand uncertainty on supply chains. Here we adopt a two-echelon supply chain model, which is basically the same as that used in the research of demand uncertainty. But the fixed lead time setting is replaced by a Markovian lead time model. Since the lead time varies with time, the dynamic characteristics of the supply chain model are different from that used in the demand uncertainty research. We make a comparison analysis of these differences from the view of dynamic systems. On the basis of the above analysis, we adopt two fundamental lemmas of the minimum variance control theory as the foundation for replenishment rules design and analysis. Then we derive formulas of the Order-up-to policy and the generalized Order-up-to policy with time-varying lead time. Moreover, we offer the variant forms of the above strategies when ...

The Impact of Uncertainty in Lead Time and Demand in Disaster Relief Supply Chains

This paper presented a system dynamics model to study the impact of uncertainty in disaster-relief supply chains. The material flows and information feedback flows of both the commercial supply chains and disaster-relief supply chains were analyzed. The structures of four types of inventory planning strategies were compared. The effect of static/dynamic lead time and constant/random demand were tested in simulations with different decision methods. The simulation results indicated that both the dynamic lead time and the random demand bring more oscillations to the supply system, and the mutual influence of them makes the behavior of a disaster-relief supply chain different from a commercial supply chain. More decision-making issues need to be considered to solve that uncertainty comes from the mutual influence.

A simulation study on strategy to mitigate leadtime uncertainty risk in the context of information sharing

Lead time is an inseparable factor of any supply chain. Lead time uncertainty is known as one of the types of supply side risks or uncertainty that affects ordering policies, inventory levels and cost, and product availability level. Information sharing between supply chain members provides opportunities to reduce the inventory levels held to face such uncertainty thereby improving the performance of the supply chain. In this context, we study the effect of sharing the information regarding replenishment leadtime on total inventory costs in a two-level supply chain. In this paper, we have proposed two-level supply chain model to analyse the effects of leadtime information and to quantify the value of the information about lead-times to the retailer. We assume that the replenishment leadtime of the supplier is random and following uniform distribution and we consider two replenishment policies the first one for the case without information sharing and the second one with information sharing. With information sharing in place the retailer exercise the strategy of employing an emergency supplier to mitigate the leadtime uncertainty. The system under consideration is formulated as a mixed integer linear programming (MILP) problem and the simulation exercise results indicate that the value of leadtime information can be significant.

Contributors

Contributors

Multi-objective supply planning for two-level assembly systems with stochastic lead times

This paper considers two-level assembly systems whose lead times of components are stochastic with known discrete random distributions. In such a system, supply planning requires determination of release dates of components at level 2 in order to minimize expected holding cost and to maximize customer service. Hnaien et al. [Hnaien F, Delorme X, Dolgui A. Multi-objective optimization for inventory control in two-level assembly systems under uncertainty of lead times. Computers and Operations Research 2010; 37:1835–43] have recently examined this problem, trying to solve it through multi-objective genetic algorithms. However, some reconsideration in their paper is unavoidable. The main problem with Hnaien et al. proposal is their wrong mathematical model. In addition, the proposed algorithms do not work properly in large-scale instances. In the current paper, this model is corrected and solved via a new approach based on NSGA-II that is called Guided NSGA-II. This approach tries to guide search toward preferable regions in the solution space. According to the statistical analyses, the guided NSGA-II has the higher performance in comparison with the basic NSGA-II used by Hnaien et al. Moreover, the wrongly reported characteristics of the Pareto front shape provided by Hnaien et al. are modified.

An international supplier selection model with inventory and transportation management decisions

In this paper, we develop a mixed integer programming model for a supplier selection problem in an international context. The main features that characterize the international supplier selection are first identified. We show that when operating in an international context, the supplier selection process should consider the following issues: several buyers’ sites; inventory decisions, in particular the safety stocks that are held by buyers to cope with the delivery lead time uncertainty; inventory capacity constraints in buyers’ sites; selection of transportation modes, each having a specific delivery frequency and a transportation capacity; and multiple products and multiple time periods. Then, we propose a supplier selection model that takes into account such characteristics and that is suited for the international context. Finally, we solve the model with the commercial optimization software Cplex and we perform computational experiments based on a realistic case study from the automotive industry in order to prove the solvability and the usefulness of the model. Sensitivity analyzes are also performed for a number of model parameters.

Optimal MRP parameters for a single item inventory with random replenishment lead time, POQ policy and service level constraint

This study deals with Material Requirement Planning (MRP) software parameterization under uncertainties. The actual lead time has random deviations; so it can be considered as a random variable. MRP approach with Periodic Order Quantity (POQ) policy is considered. The aim is to find the optimal MRP time phasing corresponding to each periodicity of the POQ policy. This is a crucial issue in supply planning with MRP approach because inappropriate planned lead times under lead time uncertainties invariably lead to large and costly inventories or insufficient customer service levels. The proposed model and algorithms minimize the sum of the setup and holding costs while satisfying a constraint on the service level. Our approach does not need to employ the commonly used normal probability distributions. Instead, its originality is in finding a closed form of the objective function, valid for any probability distribution of the actual lead times.

Component and process commonalities in production system under various uncertain factors

In this paper, the authors studied the effects of process and component/part commonality and uncertain factors (viz. lead time, machine breakdown etc.) on deliverable parameters of a multi product, multi-period and multistage dependent demand manufacturing environment. The throughput of finished products and average production time of the system are examined for various experimental scenarios on the basis of existing manufacturing setup of a company consisting of multiple end products. Simulation package, namely WITNESS is used to simulate/analyze the situations of the production lines. Simulation models are developed, verified and validated with the historical data from the company. It is found that inclusion of common components in manufacturing system is always beneficial over the non-commonality environment, especially i) in uncertain situations, ii) for long procurement lead time of components and iii) when the number of parts increase in the system. Impacts of machine breakdown on system outcomes are higher than that of the lead time variation. The combination of uncertain factors has more impact on outcomes (throughput and average production time) compared to the individual factor. Commonality has a better control over the machine breakdown than lead time uncertainty. Component commonality is more effective for a production environment under uncertain situations than the process commonality.

Dynamic robust optimal reorder point with uncertain lead time and changeable demand distribution

In fixed order quantity systems, uncertainty in lead time is expressed as a set of scenarios with occurrence probabilities, and the mean and variance in demand distribution are supposed to be changeable according to a known pattern. A new concept of “dynamic robust optimal reorder point” is proposed in this paper and its value is calculated as a “robust optimal reorder point function with respect to reorder time”. Two approaches were employed in determining the dynamic optimal reorder point. The first is a shortage rate satisfaction approach and the second is a backorder cost minimization approach. The former aims at finding the minimum value of reorder point at each reorder time which satisfies the condition that the cumulative distribution function (CDF) of shortage rate under a given set of scenarios in lead time is greater than or equal to a basic CDF of shortage rate predetermined by a decision-maker. In the latter approach, the CDF of closeness of reorder point is defined at each reorder time to express how close to the optimal reorder points under the set of scenarios, and the dynamic optimal reorder point is defined according to stochastic ordering. Some numerical examples demonstrate the features of these dynamic robust optimal reorder points.

Optimal time phasing and periodicity for MRP with POQ policy

This paper deals with component supply planning for assembly systems where several types of components are ordered from external suppliers to produce a single type of finished product. Actual component lead times are often different from those contracted because of random delays. An MRP approach with periodic order quantity (POQ) policy is used for the supply planning of components. Our aim is to find the optimal values of the order periodicity and planned lead times at the offsetting step of the MRP procedure. The goal is to minimise the sum of the average component holding, finished product backlogging and setup costs. Several theoretical properties of the objective function are proven and an efficient optimization algorithm is developed. The proofs of the explicit form and properties of the objective function as well as the development of the optimization algorithm occupy a large portion of this paper. The method developed can be used for the optimization of time phasing and periodicity for such an MRP system under lead time uncertainties.

LT variance or LT mean reduction in supply chain management: Which one has a higher impact on SC performance?

Lead time (LT) is an inseparable factor of any supply chain (SC). Lead time uncertainty is known as a type of supply uncertainty that affects ordering policies, inventory levels, and product availability level. There are two main strategies concerning SC uncertainties: adapter and shaper strategies that can be used in environments with LT uncertainty. As for LT mean, it can be reduced by improving the performance of upstream members. In this paper, relative importance of these two parameters to be reduced by these strategies is determined by investigating the effects of both LT mean and LT variance on supply chain performance indices. Simulation and multivariate models have shown that LT variance has a stronger impact on SC performance measures (including Bullwhip effect, holding inventory, stock-out size and number of stock-outs). This study can help managers in (1) rebalancing of these two parameters by applying a proper investment strategy; (2) suitable selection of service providers in transportation based on LT parameters.

To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating

AbstractThere has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. Although this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecast. To improve the accuracy of its demand forecast, a firm may update its forecast as the selling season approaches. In this article we consider both forecast updating and lead time uncertainty. We characterize the firm's optimal procurement policy, and we prove that, with multiplicative forecast revisions, the firm's optimal procurement time is independent of the demand forecast evolution but that the optimal procurement quantity is not. This leads to a number of important managerial insights into the firm's planning process. We show that the firm becomes less sensitive to lead time variability as the forecast updating process becomes more efficient. Interestingly, a forecast‐updating firm might procure earlier than a firm with no forecast updating. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009

Pre-distribution and post-distribution cross-docking operations

In this paper, we construct analytical models for distribution strategies with two major types of cross-docking, pre-distribution cross-docking (Pre-C) and post-distribution cross-docking (Post-C). A traditional distribution center system is also discussed for comparison purposes. Three models are compared pair-wisely. Analytical results show that, Pre-C is preferred for environments with shorter supply lead time and lower uncertainty of demand, without the benefits of risk-pooling. The Post-C mitigates the weakness of the Pre-C at the expense of higher operations cost spent at the cross-dock. Numerical experiments are conducted to support our results and explore other findings.