This article is an attempt to survey the vast literature on flexibility in manufacturing that has accumulated over the last 10 to 20 years. The survey begins with a brief review of the classical literature on flexibility in economics and organization theory, which provides a background for manufacturing flexibility. Several kinds of flexibilities in manufacturing are then defined carefully along with their purposes, the means to obtain them, and some suggested measurements and valuations. Then we examine the interrelationships among the several flexibilities. Various empirical studies and analytical/optimization models dealing with these flexibilities are reported and discussed. The article concludes with suggestions for some possible future research directions.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=1080305

Flexibility in Manufacturing: A Survey

A new paradigm for planning under conditions of deep uncertainty has emerged in the literature. According to this paradigm, a planner should create a strategic vision of the future, commit to short-term actions, and establish a framework to guide future actions. A plan that embodies these ideas allows for its dynamic adaptation over time to meet changing circumstances. We propose a method for decisionmaking under uncertain global and regional changes called ‘Dynamic Adaptive Policy Pathways’. We base our approach on two complementary approaches for designing adaptive plans: ‘Adaptive Policymaking’ and ‘Adaptation Pathways’. Adaptive Policymaking is a theoretical approach describing a planning process with different types of actions (e.g. ‘mitigating actions’ and ‘hedging actions’) and signposts to monitor to see if adaptation is needed. In contrast, Adaptation Pathways provides an analytical approach for exploring and sequencing a set of possible actions based on alternative external developments over time. We illustrate the Dynamic Adaptive Policy Pathways approach by producing an adaptive plan for long-term water management of the Rhine Delta in the Netherlands that takes into account the deep uncertainties about the future arising from social, political, technological, economic, and climate changes. The results suggest that it is worthwhile to further test and use the approach.

/pdf/dynamic-adaptive-policy-pathways-a-method-for-crafting-209ertb1j4.pdf

Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world

Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made the development of models for facility location under uncertainty a high priority for researchers in both the logistics and stochastic/robust optimization communities. Indeed, a large number of the approaches that have been proposed for optimization under uncertainty have been applied to facility location problems. This paper reviews the literature on stochastic and robust facility location models. Our intent is to illustrate both the rich variety of approaches for optimization under uncertainty that have appeared in the literature and their application to facility location problems. In a few instances for which examples in facility location are not available, we provide examples from the more general logistics l...

Facility Location Under Uncertainty: A Review

The checkered history of predicting the future — e.g., “Man will never fly” — has dissuaded policymakers from considering the long-term effects of decisions. New analytic methods, enabled by modern computers, transform our ability to reason about the future. The authors here demonstrate a quantitative approach to long-term policy analysis (LTPA). Robust methods enable decisionmakers to examine a vast range of futures and design adaptive strategies to be robust across them. Using sustainable development as an example, the authors discuss how these methods apply to LTPA and a wide range of decisionmaking under conditions of deep uncertainty.

/pdf/shaping-the-next-one-hundred-years-new-methods-for-3a2yh03f5w.pdf

Shaping the Next One Hundred Years: New Methods for Quantitative Long-Term Policy Analysis

The use of "optimality" as an operational research criterion is insufficiently discriminating. Ample evidence exists that for many problems simple optimization (particularly profit maximization) does not represent the aims of management. In this paper we discuss the nature of the problem situations for which alternative decision criteria are more appropriate. In particular the structure of strategic planning problems is analysed. The provisional commitment involved in a plan (in contrast to the irrevocable commitment of a decision) leads to the development of a particular criterion, robustness—a measure of the flexibility which an initial decision of a plan maintains for achieving near-optimal states in conditions of uncertainty. The robustness concept is developed through the case study of a sequential factory location problem.

Robustness and Optimality as Criteria for Strategic Decisions

This paper presents problems of resource allocation among many activities, such as allocating a given marketing budget among sales territories, where the return function for each territory attains different parameters. Applying the Kuhn-Tucker conditions, we derive “single pass” algorithms for different concave payoff functions, maximizing total returns under a given amount of available effort. Various extensions are also mentioned.

Technical Note—Allocation of Effort Resources among Competing Activities

Long-range investment plans, particularly for expansion or decentralization, often consist of a number of separate but interacting investments spaced over a number of years. Where there is appreciable uncertainty about external conditions in the future, it is possible that a “best” scheme based on the state of current knowledge will prove during the course of the intervening years to be less than good. One way of guarding against this danger is to ensure that the early (and therefore irreversible) steps in the investment sequence keep open as many options of “good” schemes as possible. Concepts of robustness and stability are developed. As a practical example of the use of these concepts a case study is presented, which deals with the location of sites for new factories in an industrial expansion program.

Robustness in Sequential Investment Decisions

For a marketing situation, mathematical models are developed expressing the relation between net revenue and the variables that affect it. These models are extensions of the ones discussed by Mills, and Krishnan and Gupta. Mills assumed that each competitor has only one controllable variable, viz., promotional effort. Krishnan and Gupta obtained equilibrium solutions for two competitors, each having two controllable variables. This paper deals with multicompetitors and discusses four models when the market potential is independent of both price and promotional effort and when it is dependent on either or both of the controllable variables.

Mathematical Models in Marketing

A model for a marketing situation with two competitors when each competitor has two control variables, price and promotional effort is presented. Mills [#84] assumed that each competitor has only one control variable, viz., promotional effort and the profit margins of the two competitors are known. In this paper the profit margins are also control variables. The paper derives conditions under which nonboundary equilibrium solutions exist and the sensitivity of the model for small deviations in the decision variables from their equilibrium values is tested. Mills’ results are found to be valid only under certain conditions.

Shiv K. Gupta

Papers

Robustness and Optimality as Criteria for Strategic Decisions

Technical Note—Allocation of Effort Resources among Competing Activities

Robustness in Sequential Investment Decisions

Mathematical Models in Marketing

Mathematical Model for a Duopolistic Market