Anthony D. Ross

A simulated annealing methodology to distribution network design and management

This paper describes the PLOT (Production, Logistics, Outbound, Transportation) design system. The system addresses a class of distribution network design problems, which is characterized by multiple product families, a central manufacturing plant site, multiple distribution center and cross-docking sites, and retail outlets (customer zones) which demand multiple units of several commodities. The resulting system focuses on two key stages: the planning stage where we incorporate a strategic based decision-making process of selecting the “best” set of distribution centers and cross-docks to operate. The second phase consists of the execution stage that includes an operational based decision-making process. In this phase, the model decides the required quantity of product families that need to be transported from the plant to distribution centers and transshipped to cross-docks from warehouses, and later distributed to customer outlets. The distribution system design considered here is derived from current operations of a major retailing organization that manages products for nationwide distribution. The PLOT system developed to implement the model provides for a high degree of user interaction in the generation of solutions. The overall system generates globally feasible, near optimal distribution system design and utilization strategies utilizing the simulated annealing (SA) methodology. This study makes two important contributions to the SA literature. First, we extend the breadth of applications by studying a new combinatorial problem that incorporates cross-docking in a supply chain environment. Second, we systematically evaluate the computational performance under a variety of problem scenarios and SA control parameter settings.

An integrated benchmarking approach to distribution center performance using DEA modeling

Abstract This research proposes an integrated benchmarking framework illustrated in the context of a large supply chain system comprised of 102 distribution centers (DCs). We employ recent extensions of data envelopment analysis while addressing difficulties often associated with empirical data in real life settings. The study measures DC productivity in a large scale setting, evaluates and identifies DCs with consistent best performance using facet analysis, and detects performance trends using window analysis of 4 years’ data. This extensive evaluation of the empirical production frontier and of “role model” DCs provided very interesting insights for strategically managing operations. Our approach opens up possible new directions for examining supply chain DCs or other activities where explicit knowledge about the relationship between the inputs and outputs is not well known.

Supplier dependence: impact on supplier's participation and performance

Purpose – The purpose of this paper is to extend our understanding of the importance of supplier dependence on the buyers firm and its relationship to supplier training and supplier involvement in product development with respect to the suppliers performance.Design/methodology/approach – A random sample of 231 firms provided the data that were analyzed for this study. Using structural equation modeling, a sub‐set of the sample consisting of 166 manufacturing firms was used to test the five hypothesized relationships in the model.Findings – The main findings indicate that supplier dependence is a significant contributor to increasing supplier participation in buyer supported training and increasing supplier involvement in product development. Also, supplier training and supplier involvement are significant contributors to the suppliers operational performance.Research limitations/implications – The model tested in this study used a random sample of US manufacturing firms. Thus, future studies should inc...

An evaluation of new heuristics for the location of cross-docks distribution centers in supply chain network design

This paper addresses an evaluation of new heuristics solution procedures for the location of cross-docks and distribution centers in supply chain network design. The model is characterized by multiple product families, a central manufacturing plant site, multiple cross-docking and distribution center sites, and retail outlets which demand multiple units of several commodities. This paper describes two heuristics that generate globally feasible, near optimal distribution system design and utilization strategies utilizing the simulated annealing (SA) methodology. This study makes two important contributions. First, we continue the study of location planning for the cross-dock and distribution center supply chain network design problem. Second, we systematically evaluate the computational performance of this network design location model under more sophisticated heuristic control parameter settings to better understand interaction effects among the various factors comprising our experimental design, and present convergence results. The central idea of the paper is to evaluate the impact of geometric control mechanism vis-a-vis more sophisticated ones on solution time, quality, and convergence for two new heuristics. Our results suggest that integrating traditional simulated annealing with TABU search is recommended for this supply chain network design and location problem.

A multi‐dimensional empirical exploration of technology investment, coordination and firm performance

As economic activities span the supply chain boundary, the effective use of technology as the medium for coordination (or integration) among and within organizations has received much attention. In the US manufacturing sector, IT usage is increasingly becoming a source of sustained competitiveness and an opportunity for improvement. And there is a growing demand to achieve conflicting performance objectives (revenue versus profitability versus efficiency, for example). This article explores the relationships between information technology investment, performance, and productivity. While management should continue to evaluate IT investments by any practical means that satisfies company needs, the development of IT competencies and investment policies so as to optimize the firm’s performance seems to be a worthwhile goal. Our empirical findings clearly suggest that IT investment has a positive impact on market performance as a result of better coordination in the value chain, but that larger investments do not seem to lead to higher financial performance. Additionally, coordination productivity seems to benefit from increased investment by reducing, say, working capital requirements. Given the diversity of firms represented, we conclude that the way in which these firms compete may also have a direct influence on the extent of IT investment and competencies.

Role of information technology and collaboration in reverse logistics supply chains

Closed-loop supply-chain channels are distribution systems that include activities supporting both the forward flow of goods from the manufacturer to the consumer as well as the reverse flow from the consumer to the manufacturer. In this paper, we identify the reverse logistics supply-chain channels, identify problems that companies face when they handle product returns along these channels and present the critical role that information technology and collaboration can play to mitigate many of the problems and deficiencies. A key element in reducing uncertainties in the different stages of the reverse channel of a supply chain is access to accurate and timely information on the status, location, and condition of products moving about in the supply chain. It is imperative that firms operating in the reverse supply-chain channels collaborate to integrate and share information in a timely fashion. We present a case study based on our interaction with two major consumer electronics companies and demonstrate how the use of radio frequency identification device technology in a warehousing operation can reduce the overall distribution costs for the organisation.

An exploratory analysis of resource utilization across organizational units: Understanding the resource‐based view

This study explores the applicability of the resource‐based view at the organizational unit level by investigating why resource utilization, as measured by efficiency, might differ within a firm. Using a downstream petroleum firm as the context for this study, the data envelopment analysis framework is applied to examine resource input congestion of its DCs (i.e. distribution centers). The study also provides a more granular analysis by decomposing distribution efficiency into managerial, scale, and programmatic efficiency, and examines the impact of corporate‐level decision making by including non‐discretionary variables. The analysis identifies opportunities to improve efficiency at the organizational unit level, using alternative views of the operational problem. The approach also provides practicing managers with an objective means to evaluate performance at the level of the organizational unit. Both the efficiency view and the managerial performance view are discussed simultaneously from a strategic view of firm resources.

Performance-based strategic resource allocation in supply networks

Abstract One driving force behind continued logistics planning research is firms’ need to maintain competitive performance and efficient resource allocation. Operations research has been instrumental in advancing logistics planning research particularly in the petroleum industry. The impact and potential of incorporating performance imperatives however, have been largely unaddressed while the problems general complexity has grown. This paper focuses on performance planning through resource allocation in supply networks by developing a profit-maximizing network model for distribution planning, and explicitly incorporating order performance criteria for distribution centers and delivery vehicles. The approach has been tested on forty realistic-sized problems, and tradeoff models provide insight and guidelines for assessing the interaction among expected profits, customer service, and operational efficiency for resource acquisition and redistribution. Managerial implications are also provided.

Benchmarking the IT productivity paradox: Recent evidence from the manufacturing sector

The production of information services is modeled using Data Envelopment Analysis (DEA) to assess the impact of information technology (IT) on productivity within the manufacturing sector. The performance issues of interest include: (1) investigating the relationship between resource allocation of IT budgets and costs such as labor (the inputs) to productivities achieved (the outputs); (2) benchmarking the relative IT-business value created in this manufacturing sector. These issues are examined by using performance data collected from Compustat(TM) databases and Information Week(TM) (IW) surveys of corporate IT executives. The results show that, through scale efficiencies, even efficient firms can improve their performance by reducing certain investments. Overall characteristics of efficient firms are provided so that other firms may emulate them in an effort to achieve benchmarked performance levels.

Nonlinear integer programming for optimal allocation in stratified sampling

A stratified random sampling plan is one in which the elements of the population are first divided into nonoverlapping groups, and then a simple random sample is selected from each group. In this paper, we focus on determining the optimal sample size of each group. We show that various versions of this problem can be transformed into a particular nonlinear program with a convex objective function, a single linear constraint, and bounded variables. Two branch and bound algorithms are presented for solving the problem. The first algorithm solves the transformed subproblems in the branch and bound tree using a variable pegging procedure. The second algorithm solves the subproblems by performing a search to identify the optimal Lagrange multiplier of the single constraint. We also present linearization and dynamic programming methods that can be used for solving the stratified sampling problem. Computational testing indicates that the pegging branch and bound algorithm is fastest for some classes of problems, and the linearization method is fastest for other classes of problems.