Problem Formulation and Solution Mechanisms: A Behavioral Study of Humanitarian Transportation Planning

When dealing with urgent, ill‐defined problems, such as rapidly evolving emergency situations, operations managers have little time for problem formulation or solution. While the mechanisms by which humans formulate and solve problems have been described, mechanisms for rapid, concurrent formulating and solving are not well understood. This study investigates these mechanisms through a field study of transportation planning in a humanitarian response setting. The findings show that the problem is solved through greedy search and formulated through sensemaking, in which search enables updates to an evolving problem formulation, and the formulation directs and limits the search process. This study explores the implications of these findings for the development of better problem formulation processes and problem‐solving strategies for urgent and ill‐defined operations management problems.     

Data mining driven DMAIC framework for improving foundry quality – a case study

Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) methodology has been widely used across industries as the best systematic and data driven problem solving approach for quality improvement. Statistical Design of Experiment (DOE) is used in the ‘Improve’ stage for obtaining optimal process settings for significant variables contributing towards quality improvement. But, DOE is an offline activity requiring time and other resources for conducting experiments and analyses. Further, there are many small and medium scale enterprises that cannot afford to conduct DOE. Under such practical constraints, it is desirable to apply DMAIC using online process data under day-to-day production situations or with little changes in process settings without compromising production. In this article, we propose a DMAIC framework, driven by data mining techniques for defect diagnosis and quality improvement where historical and online process data can be effectively utilised. We have used two decision tree algorithms namely, Classification and Regression Tree and Chi-squared Automatic Interaction Detection in developing the proposed framework. The proposed approach is applied in an Indian grey iron foundry where conducting DOE is not a feasible option for the management. The result demonstrates a significant reduction in casting defect and validates the practical viability of this approach.     

Fully Nonparametric Estimation of Scalar Diffusion Models

We propose a functional estimation procedure for homogeneous stochastic differential equations based on a discrete sample of observations and with minimal requirements on the data generating process. We show how to identify the drift and diffusion function in situations where one or the other function is considered a nuisance parameter. The asymptotic behavior of the estimators is examined as the observation frequency increases and as the time span lengthens. We prove almost sure consistency and weak convergence to mixtures of normal laws, where the mixing variates depend on the chronological local time of the underlying diffusion process, that is the random time spent by the process in the vicinity of a generic spatial point. The estimation method and asymptotic results apply to both stationary and nonstationary recurrent processes.     

A review of hierarchical production planning and its applicability for modern manufacturing

The hierarchical production planning (HPP) paradigm has become an accepted planning and control strategy for many medium-to-large manufacturing situations. While the paradigm appears intuitively obvious and appropriate for many factories, there are a number of modern manufacturing situations where the application of the HPP approach may not be appropriate. By understanding the fundamental principles and concepts inherent in the HPP approach, it is possible to identify situations suitable for HPP with little or no adaptation, and situations where HPP must be extensively modified before use. A poor understanding of HPP     

Evaluating alternative approaches to strategic planning

The question which, unfortunately, often goes unanswered, is whether a company's process of corporate planning is optimal. Furthermore, even if they wished to answer such a question there is little in the literature which can provide them with a direct, and explicit evaluative model. This paper examines the development of planning and the many different contributors towards its theoretical underpinning. Whilst recognizing that planning is a field which is a ‘semantic's jungle’ the authors carefully pick their way through the mine-field of misunderstanding and misquotation and clearly establish a base-line for evaluation and indeed propose a detailed methodology. It is hoped that this paper will be a fore-runner of many which will assist the executive in his important evaluative role concerning alternative planning approaches.     

The Ultimate Uncertainty — Intergenerational Planning

The philosophic and practical aspects of intergenerational planning for a 50-100-year time frame are reviewed, with recognition of its speculative quality. Society's near term choice of future physical pathways based on comparative quantitative benefit/cost/risk analyses of alternatives is usually modified by the intervention of a variety of time-dependent, nontechnical value systems. Further, the continuous competition among society's disparate technical systems, capital investment choices, and planning objectives all contribute to the uncertainty of the intergenerational outcome of any plan. Nevertheless, the quantitative planning process provides an essential base. Benefit/cost/risk projections are discussed for both the case with a historical database and the case without such a historical base. The end-objectives and continuous nature of such benefit/cost/risk analyses are described.     

REORDER-POINT MODELS WITH DISCRETE PROBABILITY DISTRIBUTIONS

This paper is concerned with the determination of reorder points and safety-stock levels for situations where both the demand and lead-time distributions are discrete and independent. Formulas are developed for computing exact probabilities for the lead-time demand distribution on the basis of empirical distributions. Practitioners can use the model to obtain exact probabilities for situations where the computational burden is justified, while academicians can use the model to evaluate heuristic approaches to the reorder-point problem.     

Development and analysis of mathematical and simulation models of decision-making tools for remanufacturing

This article presents decision-making tools for remanufacturing. The first decision-making tool was used to address inventory lot-sizing problems in a hybrid remanufacturing–manufacturing system with varying remanufacturing fraction. In this article, the new inventory lot-sizing model with variable remanufacturing lot sizes has been shown to exhibit better performance than the benchmark model with fixed remanufacturing lot sizes. The new inventory lot-sizing model is anticipated to become a valuable decision-making tool in companies that are planning to adopt remanufacturing. The second decision-making tool was applied to address a production and inventory planning problem in a remanufacturing system considering different remanufacturing policies for a given remanufacturing strategy. For a remanufacture-to-stock system with two quality remanufacturables groups four alternative policies were examined, a policy which specifies simultaneous processing utilising dedicated resources was shown to be the best policy to achieve a shorter remanufacturing cycle time. For a remanufacture-to-order system with two quality remanufacturables groups, the three relevant policies of the four alternative policies were examined, a policy which specifies sequential processing and switching between various quality remanufacturables groups was shown to be the best policy to achieve a shorter remanufacturing cycle time. The production and inventory planning simulation models in a remanufacturing system are expected to become significant decision-making tools in remanufacturing operations.     

New technology and the value-based management of transformational leadership

New technology is calling on people to provide adaptive responses in situations where there are many exceptions or where a high degree of variability exists or where people provide linkages between programmable segments. Further, groups of people who are geographically dispersed and unacquainted with each other will work together to solve business problems or define a process and will then disband when the job is done. Thus, the general model of responsible autonomous job behavior becomes the key facet of individual-organization-technological relationships. It is suggested that this model is best activated by the empowerment of people through the value-based management of transformational leadership.     

Planning in a state of turbulence

This paper is concerned with an exploration of the role of the long range planner, whether in the private or public sector of the economy, and the impact made upon the processes of his work by government's increasing propensity to manipulate the economy. The authors' researches over the last 2 years into the comparative nature of planning processes in the U.K. economy have made it abundantly clear to them that planners are increasingly concerned at the dangerous potential of such impact upon their forecasting procedures. The emphasis here will rest upon the planner in private enterprises, although the authors' work in both local government and the nationalized enterprises suggest that the problem is of equal importance in these sectors.The authors consider first the past nature of the search processes in long range planning and the context of such attempts to narrow down the range of variables that form the enterprise's perception of its future. Secondly, they examine the emerging discontinuity and the changing role of government, with particular reference to indicative planning concepts. Then they introduce some of the findings of a recent survey of attitudes towards long range planning in the construction industry of the U.K., a sector vitally influenced by turbulence in the economy and with particular interest in government's ideas of macro-planning. Finally Edwards and Harris examine the implications to government and to planners of their findings.     

A DYNAMIC PROGRAMMING MODEL FOR OPTIMAL ALLOCATION OF DECISION TIME

Recurrent decision making by a lower-level manager can be viewed as a sequential decision process in which time and uncertainty are limiting factors. Under these conditions, the manager must determine how to best utilize his decision making time consistent with his own particular set of decision values. A dynamic programming model was devised to determine the optimal (consistent) allocation of decision time among five different types of problems for a sequence of simulated recurrent decision situations. Fifty-one lower-level managers were interviewed about their use of decision time and decision procedures. The model was validated by comparing model assumptions and results with the findings from the interviews. The model was used to determine the effects of variations in the levels of time available and uncertainty upon the optimal allocation of decision time.     

Estimating output mix effectiveness: An applied scenario approach for the Armed Forces

The ability of public sector policy makers to prioritize has a huge impact on the effectiveness of public service provision. Public services can take the form of final outputs demanded by consumers or of intermediate outputs contributing to a process of realizing the higher goals of society. In doing the right things, policy makers choose a mix of intermediate outputs maximizing their preference value for public service outcomes, while managers do things right when responsible for producing outputs efficiently. This distinction enables us to pinpoint important reasons for inefficiencies in the provision of public services. Taking advantage of the method of scenario based planning, a model for measuring effectiveness is developed for situations where traditional methods such as two-stage regressions fail due to long time lags and lack of variation in the variables. Scenarios take the role of outcomes in the modeling of outcome mapping functions, where each scenario represents a set of environmental variables. The model is specified for the provision of defense outcomes, where the lag between changes in input and impacts on outcomes are substantial. From a sample of 12 combat units in the Norwegian Armed Forces, producing different outputs, we find that inefficiencies in output mix can explain most of the changes in overall effectiveness over a four-year period of time.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Integration of CAD/CAM and production control in sheet metal manufacturing — an application area of operations research

Abstract

This paper describes a process planning system for sheet metal parts. This system has capabilities to deliver process planning data just in time. The change of tools, processes and even machines for manufacturing of the parts is possible at the shop door after design has been finished.

The sequence of the production planning steps carried out can be changed. In this way the system can be adapted to the requirements of different sheet metal manufacturing companies.

More detailed information is given about the methods used for nesting of the workpieces on the sheets to be produced.     

Best Practices and Policy Transfer in Spatial Planning

Abstract

Numerous European programs and initiatives have been instrumental in identifying a large and increasing number of examples of best practice (or good practice) in the field of spatial planning. In fact, there is now a profligacy of best practice, which means that many researchers and policy-makers are often confronted with too much information when trying to identify examples of policy and practice in other places. The identification and dissemination of best practices has become a growing industry in many areas of European policy, including spatial planning and urban environmental issues. In many cases, an underlying assumption of best practices is that they are equally applicable and effective in another setting, and that the development and dissemination of best practice will help to lead to improvements in policy and practice in other countries, regions or cities. However, the reality is that best practices have a more limited role in policy-making processes: other influences are frequently more important. The value of exchanging European best practices is limited since there are huge differences in the economic, political or social situation between countries in the European Union. This is particularly true when considering the transfer of best practices between ‘new’ and ‘old’ member states, where the social and economic situation, as well as the institutional frameworks, are often very different in ‘borrowing’ and ‘lending’ countries.     

METHODS FOR QUANTIFYING SUBJECTIVE PROBABILITIES AND MULTI-ATTRIBUTE UTILITIES*†

In many situations where normative decision-aiding techniques could be usefully applied, historical data are inadequate for estimating the required outcome probabilities, and economic methodologies are inadequate for estimating the aggregate utility derived from the several outcome attributes. In such cases it is often useful to obtain the required estimates in the form of expert judgments, i.e. to obtain subjective probabilities and multi-attribute utilities. Similarly, in many situations where behavioral decision processes are to be studied, it is necessary to scale the expectations and perceived values of the decision makers. This article describes the methods for eliciting subjective probabilities and multi-attribute utilities whose usefulness has been empirically studied and reported in the research literature. It also contains summary guidelines concerning the elicitation and use of such judgments.     

Tactical production and distribution planning with dependency issues on the production process

Tactical production-distribution planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.     

商业银行流动性风险管理方法的改进研究——基于模糊定性约束下的动态规划补偿模型应用

商业银行流动性管理一向受银行管理者重视。管理银行流动性的方法大多采用运筹学规划,前提假定是这些参数为确定性的,或运用历史数据回归来确定随机参数的分布规律。但现实中,这些参数常为不确定的,且不存在概率分布的统计基础,致使决策结果有悖科学化。本文提出一种解决此问题的改进方法:首先建立不确定参数的模糊集,然后再将其转换成确定性分布嵌入动态规划的模型中,构建了多阶段动态线性规划补偿模型。通过改变模型中的部分参数,模型就能灵活地给出不同风险偏好的管理者的流动性管理策略选择。     

SELECTING PARAMETERS FOR SHORT-TERM FORECASTING TECHNIQUES

The objective of this paper is to discover which of three forecasting modes used to select parameters for four short-term forecasting techniques minimizes errors. The study also examines whether the amount of historical data used to find parameters contributes to forecasting success. The results show the traditional one-ahead search routine works well in some, but not all, forecasting situations. Also, forecasting errors appear to decline when more historical data are included in the parameter search.     

Planning for water resources

In this article the author describes some of the problems of planning for water resources, and the way in which the recently established Thames Water Authority has organized itself to deal with them. He demonstrates that water resource planning is involved with the whole of the water cycle, and is largely concerned with harnessing and controlling natural phenomena in situations of uncertainty.