Tan Miller

Equilibrium facility location on networks

1 Introduction.- 2 Aspatial Stackelberg Nash Cournot Equilibria.- 3 Classical Plant Location on Networks.- 4 Spatial Market Equilibria on Networks.- 5 Sensitivity Analysis of Spatial Market Equilibria on Networks.- 6 A Facility Sizing and Location in Spatial Price Equilibrium Model.- 7 Stackelberg Equilibria on Networks.- 8 A Facility Sizing and Location in Stackelberg Nash Cournot Equilibrium Model.- 9 The Importance of Including Reaction Functions and Analysis of Economic Equilibria in Facility Location Models: An Example.- 10 Dynamic Models: Equilibrium and Disequilibrium Approaches.- 11 Conclusion.- List of Figures.- List of Tables.

Existence theory for spatially competitive network facility location models

Models for locating a firms production facilities while simultaneously determining production levels at these facilities and shipping patterns so as to maximize the firms profits are presented. In these models, existing firms, are assumed to act in accordance with an appropriate model of spatial equilibrium. A proof of existence of a solution to the combined location-equilibrium problem is provided.

Incorporating competitors' reactions in facility location decisions: A market equilibrium approach

Abstract When a firm locates a new plant, and begins producing and shipping product to markets, this typically stimulates reactions by other firms supplying those markets. This suggests that to truly make a profit maximizing location decision, a firm must anticipate the markets reaction in the location decision-making process. In this paper, we review the development of a class of models designed to determine the profit maximizing location decision for a firm seeking to establish a manufacturing facility (or facilities) on a network characterized by either competitive or oligopolistic economic competition. One particular model from this class is presented, and the importance of anticipating the reaction to a location decision is illustrated through numerical examples of the model.

Transport network design and mode choice modeling for automobile distribution: A case study

Abstract This paper describes the development and implementation of a mixed integer programming type model designed to determine the best transport mode and rail network location strategy for a leading international automobile manufacturer to supply its North American dealers. In particular, this manufacturer wished to establish a plan for its future vehicle distribution that would determine the best mix of truck, conventional rail and containerized intermodal rail to transport cars and light trucks from its North American plants and ports of entry to its dealers. Further, the manufacturer desired to evaluate the proper number, types and locations of rail terminals required for its distribution network. This paper is intended to provide a perspective on the practical application side of this study and how one can conduct such studies in a condensed time period. Thus, in addition to describing the study problem, results and benefits, we also emphasize such topics as how one can manipulate relatively “user friendly” commercial software to address potentially complex mode choice and location problems.

Formation of a strategic manufacturing and distribution network with transfer prices

We propose a profit maximization model for the decision support system of a firm that wishes to establish or rationalize a multinational manufacturing and distribution network to produce and deliver finished goods from sources to consumers. The model simultaneously evaluates all traditional location factors in a manufacturing and distribution network design problem and sets intra-firm transfer prices that take account of tax and exchange rate differentials between countries. Utilizing the generalized Benders decomposition approach, we exploit the partition between the product flow and the cash allocation (i.e., the pricing and revenue assignment) decisions in the supply chain to find near optimal model solutions. Our proposed profit maximizing strategic planning model produces intuitive results. We offer computational experiments to illustrate the potential valuable guidance the model can provide to a firms supply chain design strategic planning process.

A logistics deployment decision support system at Pfizer

We constructed a decision-support-system (DSS) to help the distribution network of Pfizer plan the daily deployment of finished goods inventory across its network. Utilizing databases, programming languages, spreadsheets and data inputs from the firm’s ERP; this system guides daily shipments of critical inventory between plants, distribution centers and copackers. This DSS improved the firm’s ability to effectively utilize its storage capacity and meet customer shipping requirements across a widely dispersed network.

Supply chain planning : practical frameworks for superior performance

The book is divided into three sections. The first offers the novice, while reminding those acquainted with the subject, how culture acts as the prime driver of our life - the filter of our senses and the guide of our values hence the measurement barometer upon which all our decisions and behavior is constructed. The use of culture in a commercial setting is introduced with research generated guidelines to complete the introduction for managers. The next section examines how cross cultural determinants should function as a worthwhile tool in cross cultural engagement proposing a two-step concentration. Firstly if we are different, what is the degree of separation, a step to getting people to recognize that diverse societies are not necessarily polar opposites, black and white programmed absolutes, as there exists a grey space of shared common ground.

Notes On Using Optimization And DSS Techniques to Support Supply Chain And Logistics Operations

In this chapter, we offer recommendations on approaches that can further the rate of use of optimization and related methods in firms that may not have a rich history of utilizing these types of techniques. We begin by reviewing a framework for organizing operations from the strategic level to the daily operating level. Next, we consider traditional opportunities to employ optimization and related methods across this framework of activities. We then describe a general operating approach to facilitate the use of optimization and related decision support system (DSS) methods as a standard business practice. Finally, “lessons learned” from the author’s implementation of DSS in several industries are discussed.

Outbound Logistics Performance and Profitability: Taxonomy ofManufacturing and Service Organizations

This paper develops a taxonomy of manufacturing and service firms formed by their emphasis on different key performance metrics to monitor and manage the outbound logistics portion of the supply chain. Furthermore, this study determines whether the use of specific key metrics by firms in these different classifications varies by industry, and what effect, if any, the varying emphases on different key performance metrics within classifications have on firm financial performance. The original data for this study were obtained from SAPs Benchmarking Program for Supply Chain Planning and utilizes performance metrics data from 247 manufacturing and service firms. Cluster analysis was used to develop a taxonomy based on the outbound logistics metrics. Four clusters were found to be distinct and well-formed and emphasize different sets of outbound logistics performance metrics. The clusters were named Inventory Investment Minimizers; Low Cost, Low Service Providers; Planners and Efficient Distribution Spenders; and Heavy Distribution Spenders. This study evaluated whether the emphasis on specific sets of outbound logistics performance metrics tends to be associated with firms in specific industries, and whether differences in firm financial performance, as measured by net operating margin, were found across clusters. This is the first effort to investigate whether a taxonomy of firms can be developed based on the firms’ use of different performance metrics to monitor and manage outbound logistics.