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Über dieses Buch

This work encapsulates the essential developments in this field into a single resource, as well as to set an agenda for further development in the field. This brief focuses on the demand flexibility in supply chains with fragmented results distributed throughout the literature. These results have strong implications for managing real-world complex operations planning problems.

This book exploits dimensions of demand flexibility in supply chains and characterizes the best fit between demand properties and operations capabilities and constraints. The origins and seminal works are traced in integrated demand and operations planning and an in-depth documentation is provided for the current state of the art. Systems with inherent costs and constraints that must respond to some set of demands at a minimum cost are examined. Crucial unanswered questions are explored and the high-value research directions are highlighted for both practice and for the development of new and interesting optimization models and algorithms.

Inhaltsverzeichnis

Frontmatter

Supply Chain Operations Models with Demand Shaping

Frontmatter

Chapter 1. Scope of Problem Coverage and Introduction

Abstract
This chapter begins with an introduction to the book’s scope and preliminary concepts applied throughout the book. We then present a set of basic, foundational, and classical models from the operations planning literature that serve as the underpinning of the work presented throughout the book. These models include the economic order quantity (EOQ), the newsvendor problem, the economic lot-sizing problem (ELSP), the knapsack problem (KP), the generalized assignment problem (GAP), and the facility location problem (FLP). The main results presented later in this book generalize these classical models to account for a planner’s ability to influence demands, which have traditionally served as fixed parameters in these foundational models.
Joseph Geunes

Chapter 2. Production and Inventory Planning Models with Demand Shaping

Abstract
This chapter considers the state of prior literature on operations models that account for demand flexibility. In particular, we focus on generalizations of the models discussed in Chap. 1 that treat demands as decision variables. These generalizations typically involve pricing models, and they provide a foundation for the models we will study in subsequent chapters.
Joseph Geunes

Production Planning with Demand Flexibility

Frontmatter

Chapter 3. EOQ-Type Models with Demand Selection

Abstract
This chapter discusses a generalized version of the economic order quantity (EOQ). In particular, we consider a situation in which a single inventory stage must select from among a set of demand streams, those which it will satisfy. Each demand stream carries with it a constant demand rate as well as a constant revenue rate. We consider several problem variants within this class, including problems with lot size and demand rate constraints.
Joseph Geunes

Chapter 4. Single-Period Stochastic Inventory Planning with Demand Selection

Abstract
This chapter deals with a generalization of the single-period newsvendor problem. We consider a setting in which a decision maker at a single stocking point must determine the stock level for a single product under uncertain demand. In addition to determining the item’s stock level, the decision maker must select a subset from a set of individual demands, each of which is uncertain and follows a particular probability distribution. Assuming normally distributed and independent demand streams results in a class of problems that are strikingly similar to the problems considered in the previous chapter, although the underlying model assumptions are quite different.
Joseph Geunes

Chapter 5. Dynamic Lot Sizing with Demand Selection and the Pricing Analog

Abstract
This chapter defines a model for production planning for a single product in a periodic setting, where the planner must select from a number of individual orders for the product. Associated with any order are a demand quantity, delivery period, and revenue. Acceptance of an order implies that it must be met on time and in full. Orders are placed in advance of the planning horizon, and the planner must determine which orders to accept as well as a production plan for meeting these orders on time over a finite horizon. Production in any period carries a fixed order cost as well as variable production costs, and inventory may be held from period to period, incurring an associated holding cost. The planner’s goal is to maximize profit from order acceptance decisions over the planning horizon.
Joseph Geunes

Chapter 6. Dynamic Lot Sizing with Market Selection

Abstract
This chapter considers a seemingly innocuous change in the assumptions underlying the Demand Selection Problem (DSP) considered in the previous chapter, which severely complicates the problem analysis. Instead of a sequence of independent demands over a time horizon, in this variant of the problem, demands in successive periods may be related in the sense that if we satisfy a given demand in some period t, we must then satisfy a particular set of demands in other periods. That is, instead of selecting individual demands, we are now faced with the problem of selecting from a set of time-phased vectors of demands. In practical terms, this corresponds to determining whether we will satisfy all or none of a given customer’s or market’s demands over the time horizon. We refer to the resulting problem as the Market Selection Problem (MSP) and discuss the problem’s complexity and potential solution approaches throughout this chapter.
Joseph Geunes

Supply Chain Network Planning with Demand Flexibility

Frontmatter

Chapter 7. Assignment and Location Problems in Supply Chains

Abstract
This chapter delves into problems that require assigning customer demands to supply sources. When no fixed cost exists for using a supply source and supply sources are capacitated, we have a generalized assignment problem (GAP). When fixed costs are incurred for using a supply source, then the problem is a classical facility location problem (FLP). We consider both capacitated and uncapacitated facility location problems, as well as the implications of requiring single sourcing constraints that do not allow splitting a demand between supply sources. Within these problem classes, we analyze two different forms of demand flexibility. The first type of flexibility corresponds to what we saw in the last two chapters, i.e., each demand must be either fully accepted or rejected. The second type of flexibility requires satisfying each demand, but the quantity (e.g., size, number of units) at which a demand is satisfied must fall between prespecified lower and upper limits, while revenue is proportional to the level at which the demand is satisfied. This chapter defines several such assignment and location models containing these dimensions of demand flexibility.
Joseph Geunes

Chapter 8. Branch-and-Price Decomposition for Assignment and Location Problems

Abstract
This chapter addresses a number of models with an assignment-based structure that require allocating a set of demands to a set of resources. While we have already considered several types of assignment problem in previous chapters, each of these previous models assumed that a specific assignment cost could be specified a priori, which depends only on the particular demand and the resource to which it is assigned. In contrast, for the models considered in this chapter, the costs associated with a resource will sometimes depend on the collective set of demands assigned to the resource. The primary approach applied for solving these problems will be a branch-and-price decomposition method. Of particular interest in applying this approach are the so-called pricing problems that arise in the decomposition. As we will see, these pricing problems will be consistent with several of the models defined and analyzed in previous chapters.
Joseph Geunes

Research Directions and Modeling Challenges

Frontmatter

Chapter 9. Research Challenges in Supply Chain Planning with Flexible Demand

Abstract
This chapter discusses the limitations of the models we have discussed throughout the book, and uses these limitations to characterize challenging future research directions. In doing so, we discuss the relation of the models we have considered to practice, and their potential for use in practical applications. We also consider the potential for expanding the definition of demand flexibility, as well as the technical difficulties inherent in meeting the challenges implied by potential future research avenues.
Joseph Geunes
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