Mark C. Springer

Measuring endogenous supply chain volatility: Beyond the bullwhip effect

Most recent research on supply chain volatility has focused on one particular dimension of that volatility, namely the amplification of upstream order variability. While not ignoring this aspect of supply chain volatility, we focus on a different but equally critical aspect of volatility: the cyclical oscillation of on-hand and on-order inventories about their target values. We prove that such cyclicality does not require oscillatory or random retailer demand as a prerequisite; the resulting volatility is therefore endogenous rather than simply an amplification of exogenous demand inputs. We also measure the amount of amplification resulting from a step increase in demand. The order amplification is the product of two factors, each of which is clearly linked to either on-hand or on-order inventory. Our results attest that supply chain volatility can arise in the absence of exogenous oscillatory or random demand and suggest strategies for avoiding or minimizing such volatility.

Managing the order pipeline to reduce supply chain volatility

The bullwhip effect in particular, and supply chain volatility in general, has been the subject of much analytical and empirical investigation by researchers. One goal of this work has been to determine supply chain designs and policies that minimize volatility. Using a system dynamics approach, we use three distinct supply chain volatility metrics to compare the ability of two alternative pipeline inventory management policies to respond to a demand shock. The results indicate that no one policy dominates on all three metrics of supply chain volatility. A simplistic static pipeline policy minimizes the bullwhip effect and lessens the likelihood of on-hand inventory oscillations, while a more sophisticated dynamic pipeline policy may converge more rapidly to the new equilibrium. In addition, simulation results suggest that the dynamic policy provides better customer service through fewer stockouts and backorders.

New complexity measures for the facility layout problem: an empirical study using traditional and neural network analysis

Abstract The most frequent application of the quadratic assignment problem has been in facility layout, which is concerned with locating the activities or departments of an organization in a fixed set of locations such that those activities with the strongest interrelationships are closest to each other. Early attempts to explain the varying performance of optimal and heuristic solution procedures on different layout problems focused on a univariate complexity measure such as the coefficient of variation. Recently, a multivariate measure for assessing the complexity of the quadratic assignment problem (QAP) formulation of the facility layout problem has been proposed. This paper introduces a new thresholding procedure for capturing critical relationship information, expands the eight components of the multivariate complexity measure by adding two new components, demonstrates a new solution value bound and experimentally determines the effect on solution quality of using either one of two heuristic solution procedures versus an optimal procedure. This result is important because it enables layout planners to determine in advance the likelihood of obtaining an optimal solution. It also tells them which problem characteristics are important and their relative weights in determining the solution outcome.

Queueing Models for Performance Analysis: Selection of Single Station Models

Abstract Queueing networks are increasingl being used in facility planning to evaluate alternatives. The foundation of such models is an accurate approximation of the single-station queue. Several alternative models have beenn proposed for the single-station queue with fini buffers and general arrival and service processes. This paper compares five such approximations by examining how the values of the queue parameters impact the performance methods are shown to be more accurate and less biased than alternative approximations.

A Decomposition Approximation for Finite-Buffered Flow Lines of Exponential Queues

Abstract Tandem queueing networks may be used as an alternative to simulation in evaluating the performance of proposed flow lines with finite work-in-process buffers. A new approximation is proposed for estimating the throughput rate and work-in-process inventory of finite-buffered exponential queues in series. The approximation is applied to several sets of previously published test problems and is shown to consistently perform well relative to existing models. In addition, a large simulation experiment is conducted to examine the robustness of the approximation under a wide range of parameter settings.