Decision support for hospital evacuation and emergency response

Evacuation planning is an important part of a hospital’s emergency management plan. In an evacuation the safety and health of patients is the fundamental success parameter. Thus, in this paper we introduce an evacuation model, appropriate for planning and operations, that has the objective of minimizing expected risk, both the threat risk that is forcing the evacuation, and the risk inherent in transporting patients, some in critical condition. Specifically, we study the allocation of patients, categorized by criticality and care requirements, to a limited fleet of vehicles of various capacities and medical capabilities, to be transported to appropriate receiving hospitals considering the current available space in each hospital for each category of patient. The model is an integer program, where the non-linear expected risks are calculated a-priori. This model has a structure that has excellent solution characteristics that permit us to solve large problems in a reasonable time, enabling the model to potentially be used for both planning and operations. To illustrate the solvability of this model and demonstrate its characteristics, we apply it to a realistic case study based on the evacuation of a large regional hospital.     

Criticality in Stochastic Networks

The common definition of ‘criticality’ in stochastic networks is insufficiently general, and often counter-intuitive. An alternative metric, ‘cruciality’ has been proposed. The combination of the common criticality metric and cruciality is shown to provide information about the ‘uncertainty impact’ and ‘controllable benefit’ in the network.     

Contagion in cyber security attacks

Systems security is essential for the efficient operation of all organizations. Indeed, most large firms employ a designated ‘Chief Information Security Officer’ to coordinate the operational aspects of the organization’s information security. Part of this role is in planning investment responses to information security threats against the firm’s corporate network infrastructure. To this end, we develop and estimate a vector equation system of threats to 10 important IP services, using industry standard SANS data on threats to various components of a firm’s information system over the period January 2003 – February 2011. Our results reveal strong evidence of contagion between such attacks, with attacks on ssh and Secure Web Server indicating increased attack activity on other ports. Security managers who ignore such contagious inter-relationships may underestimate the underlying risk to their systems’ defence of security attributes, such as sensitivity and criticality, and thus delay appropriate information security investments.     

Calculating the Rate of Occurrence of Failures for Continuous-time Markov Chains with Application to a Two-component Parallel System

In this paper, we assume that a system process is either a continuous-time Markov chain or a higher dimensional Markov process after introducing some supplementary variables. A formula for evaluating the rate of occurrence of failures is derived. As an application, a maintenance model for a two-component parallel system, in which component 1 after repair is not ‘as good as new’ but component 2 after repair is ‘as good as new’, is studied.     

Developing a Visual Interactive Model for Corporate Cash Management

The operational research/management science journals contain an extensive literature that addresses the corporate cash management problem; yet few, if any, companies make use of any of this published work in their daily cash-management decision making. A review of the literature suggests that the reason for this lack of applications may well be poor problem formulation—the problems that are solved in the literature as ‘cash management’ problems evolve from a ‘hard systems’ view of real-world cash management. However, the problem as perceived by cash managers involves both dynamic and loosely structured components which are difficult to model using classical (i.e. ‘hard systems’) approaches.We therefore decided to approach the cash management problem as an experiment in the use of a novel visual interactive problem solving (VIPS) methodology. The aim of the experiment was to develop an implementable, visual interactive model to support daily cash management decision making. Working closely with a corporate cash manager, we first developed a visual model of his daily decision problem and then agreed on the feasible options and the interactive requirements. At this stage, the problem was sufficiently well defined for a mathematical model to be built and the visual model made ‘smart’.This paper discusses the results of this experiment and suggests that VIPS may have distinct advantages as a problem-solving technique in loosely structured, ‘messy’ problem situations.     

Detecting inefficiently managed categories in a retail store

Growth in operational complexity is a worldwide reality in the retail industry. One of the most tangible expressions of this phenomenon is the vast increase in the number of products offered. To cope with this problem, the industry has developed the ‘category management’ approach, in which groups of products with certain common characteristics are grouped together into ‘categories’, managed as if they were independent business units. In this paper, we propose a model to evaluate relative category performance in a retail store, considering they might have different business objectives. Our approach is based on Data Envelopment Analysis techniques and requires a careful definition of the resources that categories use to contribute to achieving their business objectives. We illustrate how to use our approach by applying it to the evaluation of several categories in a South American supermarket. The empirical results show that, even for very conservative assumptions, the model has a significant discriminatory power, identifying 25% of the sample as not operating efficiently. Although efficiency scores might exhibit a relatively large dispersion, the set of efficient units is robust to data variations.     

THE VALUE OF SHORT‐RUN CLIMATE FORECASTS IN MANAGING THE COASTAL COHO SALMON (ONCORHYNCHUS KISUTCH) FISHERY IN WASHINGTON STATE

ABSTRACT. . In recent years our understanding of the intricate connections between climate variability, marine and freshwater environmental conditions and the responses of fish stocks has improved considerably. With predictable relationships between the environment and stock abundance, fishery managers should be able to forecast variation in stock survival and recruitment. Such forecasts present an opportunity for increasing the economic value of fisheries and for achieving other management objectives, such as stock conservation and maintenance of population diversity. After describing a 4‐step framework for addressing the question ‘What is a forecast worth?’ in a fishery decision‐making context, we introduce the management system for Washington's coastal coho salmon (Oncorhynchus kisutch) fishery. Then we apply the 4‐step framework to estimate the value of improved run size forecasts in the annual harvest management of coho salmon in Washington State. Our principal analytical tool is a stochastic simulation model that incorporates the main characteristics of the fishery. The paper concludes with a discussion of opportunities and constraints to the use of climate‐based forecasts in fishery management on various spatial and temporal scales, and we consider the challenges associated with forecasting variations in fish stock size caused by shifts in climate and related ocean conditions.     

KIBS员工需求驱动下行为决策的模拟——基于风险偏好视角

随着经济全球化的发展,知识密集型服务业(KIBS)越来越受到学术界的关注。本文研究员工的风险偏好对KIBS员工合作与冲突行为的影响演化规律,目的在于为KIBS的管理决策提供支持。为了发现风险偏好对员工合作与冲突行为的影响,设计效用函数,并建立了风险规避和风险中性下KIBS员工合作与冲突行为决策模型,给出了KIBS员工在不同风险假定下的最优行为决策,对风险规避员工组织应当给予适度的激励,这样能够提高员工的合作程度。之后使用MATLAB2010进行模拟,并使用EXCEL对数据进行分析,发现:(1)风险偏好程度不同对员工的决策行为的影响程度不同;(2)对于员工应该给予适当的激励措施,以便提高员工的合作程度;(3)当任务的工作量达到一定程度,应当增加的是员工的固定收益而不是激励程度。     

A hybrid maintenance model with imperfect inspection for a system with deterioration and Poisson failure

A new maintenance model for a system with both deterioration and Poisson failures is proposed. In this model, at any time-instant G _S and when the system is operating, one of the following decisions may be taken: (1) stop the system to perform a scheduled minimal maintenance; (2) stop the system to perform an inspection; and (3) no action and allow the system to go on with its operation. Following an inspection, based on the deterioration condition of the system, one of the following decisions may be taken: (a) if the system is in a ‘good’ condition, no maintenance action is taken and a number of periodic minimal maintenance activities are scheduled, starting T1 later; (b) if the system is in an ‘intermediate’ condition, a minimal maintenance is performed and an inspection is scheduled for T2 later (T2 < T1); and (c) if the system is in a ‘bad’ condition, a major maintenance is performed and a number of periodic minimal maintenances are scheduled, starting T1 later. In addition, a deterioration failure is restored by a major repair and a Poisson failure is restored by a minimal repair. Generalised stochastic Petri nets are used to represent and analyse the model, which represents a ‘composite’ maintenance strategy. Based on maximisation of the throughput of the system the benefit of this model compared to (1) an equivalent periodic inspection model and (2) an equivalent planned scheduled maintenance model, is demonstrated. This study presents a new hybrid model with a general framework for incorporating various types of maintenance policies. Also by incorporation of a number of features, this model will be more applicable to real world technical systems (complex systems), although it can be applied to individual components that are part of a complex system.     

Efficient frontier cutoff policies in credit portfolios

Historically, account acquisition in scored retail credit and loan portfolios has focused on risk management in the sense of minimizing default losses. We believe that acquisition policies should focus on a broader set of business measures that explicitly recognize tradeoffs between conflicting objectives of losses, volume and profit. Typical business challenges are: ‘How do I maximize portfolio profit while keeping acceptance rate (volume, size) at acceptable levels?’ ‘How do I maximize profit without incurring default losses above a given level?’ ‘How do I minimize the risk of large loss exposures for a given market share?’ In this paper we are not concerned with which combination of objectives are appropriate, but rather focus on the cutoff policies that allow us to capture a number of different portfolio objectives. When there are conflicting objectives we show that optimal policies yield meaningful tradeoffs and efficient frontiers and that optimal shadow prices allow us to develop risk-adjusted tradeoffs between profit and market share. Some of the graphical solutions that we obtain are simple to derive and easy to understand without explicit mathematical formulations but even simple constraints may require formal use of non-linear programming techniques. We concentrate on models and insights that yield decision strategies and cutoff policies rather than the techniques for developing good predictors.     

The Efficiency of Two Groups of <Emphasis Type="Italic">N</Emphasis> Machines Served by a Single Robot

Many modern manufacturing facilities use carousel conveyors for storage of work-in-progress, and automatic devices to place and retrieve items in and from the storage locations. The ‘carousel conveyor problem’ is directly related to the ‘patrolling repairman problem’ reported by others. In this paper, we extend the model to include a single robot serving two or more carousels. The approach makes use of known results for the patrolling repairman.     

Budget and long-range planning in public transportation — An applicative linear programming model

Economic and financial planning is an actual problem for Italian Transport Authorities, since in Italy there are scarce financial resources, to cover either the difference between costs and fares proceeds or investment needs. The proposed model is ‘just tailored’ on public transport, subjected to the Italian laws; it takes into account the particular activities (‘functions’) connected with public transport operating (e.g.: fare collection, service production, maintenance, purchases, inventories, administration). Each function is considered as a ‘module’ with its own constraints, and it is connected with the other ‘modules’, so that we can get a ‘representative’ model. Also the most significant parameters of the ‘public transport operating problem’ (e.g.: vehicle miles, passenger journeys, number of vehicles, number of employees, and so on) are connected one another. Since all relations and constraints, connecting the ‘problem variables’ can be represented as linear, the model structure is based on linear programming; this fact allows to pursue an optimum for one or more objective functions, each of them identifing an operational policy. So it is possible to connect simulation with optimization. A multi-period model can be used for long-range planning, pursuing a multi-year optimum; this is the most significant use. The Administrative Module contains Balance-Sheet, Cash-Flow, Profit and Loss Account, which are ‘constraints’ in the model and are expressed as Italian financial laws require; this structure is one of the main characteristics. Modules' dimensions and additional constraints (e.g. economic or financial ratios, fare level, turnover of inventories, and so on) can be ‘tailored’ on each particular case, driving the model towards more realistic solutions.     

CHILDREN'S PROPORTIONAL REASONING AND TENDENCY FOR AN ADDITIVE STRATEGY: THE ROLE OF MODELS

In this paper we report on 10 –14 year old children's strategies while solving two versions of ratio and proportion tasks: one ‘with models’ thought to facilitate proportional reasoning and one ‘without’. Rasch methodology was used to develop ‘with’ and ‘without models’ test versions which were given to a linked sample involving 673 children. We examine the pupils’ additive errors, their effect on ratio reasoning and how contingent on ‘model’ presentation this is. First, we provide a single scale on which pupils, item-difficulty and additive errors can be located. We then provide a new scale constructed from the error prone items, which we name the ‘tendency for additive strategy’. The measurement data is supported by qualitative data showing that the presence of ‘models’ can sometimes affect children's strategies, both positively and negatively but rarely makes a significant measurement difference on this, untutored, sample.     

Medical device maintenance outsourcing: Have operation management research and management theories forgotten the medical engineering community? A mapping review

In this paper, we examine the large body of existing research on outsourcing, and assess the status of research on outsourcing the maintenance of medical devices. Because so little research in this area currently exists, the study was broadened to include other fields that outsource maintenance services, and considers possible applications to the field of medical device maintenance. In all, this paper examines 55 articles spanning various dimensions, including: mathematical models, empirical studies, and conceptual papers. We conclude that research into the outsourcing of medical device maintenance services in hospitals is still in its infancy stages, and that further progress in this field would benefit from additional empirical study grounded in management theory.     

Synchronization in supply chains: implications for design and management

Supply chain management literature calls for coordination between the different members of the chain. Materials should be moved from one supplier to the next according to a just-in-time schedule. In this paper, we show that for many supply chain configurations, complete synchronization will result in some members of the chain being ‘losers’ in terms of cost. We develop an algorithm for optimal synchronization of supply chains and provide some guidelines for incentive alignment along the supply chain. In developing the model, we use the economic delivery and scheduling problem model and analyze supply chains dealing with single and multiple components. For single-component supply chains, we derive a closed-form expression for the optimal synchronized cycle time. For multi-component supply chains, we develop an algorithm for finding the optimal synchronized cycle time. We test the performance of the algorithm and show that it provides optimal solutions for a wide range of problems. We illustrate the models with numerical examples.     

On a Resurgence of Management Simulations and Games

The past few years have seen a significant resurgence of interest in ‘management games’ and ‘management flight simulators’, one particularly active source of such work being the system dynamics community. After proposing a distinction between games and simulations, this paper provides some background to these developments by briefly describing the historical roots of the field and the fundamental ideas of the system dynamics community, which are now giving rise to ‘microworlds’. The training advantages of management simulations and games are then discussed. The paper closes with a note on the research and findings of the system dynamics field and by offering some words of warning on the perils of simulation and game use. Two scenarios for how the use of simulations and games as management education devices might develop in the future are proposed. An Appendix describes five examples of very different types of management simulations and games.     

Adapting and refining in multi-criteria decision-making

This paper describes the implementation of a Structured Methodology for Direct-Interactive Structured-Criteria (DISC) Multi-Criteria Decision-Making (MCDM), an eight-stage nomological adjusting cycle of activities that shape the information used to make a decision, requiring it be accessible, differentiable, abstractable, understandable, verifiable, measurable, refinable and usable. It shows, in a major IT strategic investment case, that Structured DISC MCDM provides a robust model that can be used for deep and serious consideration of multi-criteria decisions by a group of decision-makers over a long period. The paper describes the case as it moves through stages of the adjusting cycle and shows that, after completing the cycle, it reverses and becomes an adapting process, starting with refining the information. Refining is shown to be more extensive than previously understood, and to cover ‘alternatives & scores’, ‘criteria & weights’ and ‘set of alternatives’. Next the form of measurement is adapted. As the number of alternatives are reduced it can become more appropriate to directly compare the two or three most preferred alternatives relative to one another rather than objectively. Finally the criteria tree can be adapted using a ‘magnifying glass’ approach. This confines the evaluation to that part of the criteria tree in which the difference between a few preferred alternatives is mainly emphasised.     

First,do no harm? A framework for evaluating new <Emphasis Type="Italic">versus</Emphasis> reprocessed medical devices

More than ever before, health care providers are under intense pressure to control costs. Medical devices represent a significant ‘hard’ cost, with worldwide spending exceeding USD 235 billion. A growing number of health care providers are engaging in the practice of reprocessing—sterilizing and reusing medical devices labelled only for a single use. The ethical and technical dimensions of this practice have received much attention, but its economic aspects remain largely unexamined. This paper presents a Markov decision process framework that a health care provider can use to decide whether to use new or reprocessed devices in a given context. Two cases are studied: completely observable device condition and partially observable device condition. After briefly discussing structural results for the two cases, several examples are presented to illustrate how the model can be applied in practice. Useful results can be computed quickly with minimal data. A key insight of the model is that perfect information regarding the device condition is often not required to make a sound decision.     

A revenue management approach to address a truck rental problem

This paper describes an application of revenue management techniques and policies in the field of logistics and distribution. In particular, the problem of transportation operators, who offer products for hire, is considered. A product is a truck of a given capacity, which can be rented for one or several time periods, throughout a multi-period planning horizon. The logistic operator can satisfy the demand of a given product with trucks with a capacity greater than that initially required, that is an ‘upgrade’ can take place. In this context, the logistic operator has to decide whether to accept or reject a request and which type of truck should be used to address it. For this purpose, a dynamic programming (DP) formulation of the problem under consideration is devised. The ‘course of dimensionality’ leads to the necessity of introducing different mathematical programming models to represent the problem. The mathematical models we presented are an extension of the well-known approximations for the DP of traditional network capacity management analysis. Based on these models and exploiting revenue management concepts, primal and dual acceptance policies are developed and compared in a computational study.     

Weight assurance region in two-stage additive efficiency decomposition DEA model: an application to school data

In this paper we use the additive efficiency decomposition approach in two-stage data envelopment analysis. Initially, we evaluate the variable returns to scale version and face a structural difficulty of the model. In an extreme case, weights ξ₁ or ξ₂, which represent the relative importance of the performance of the first and second stages, respectively, become zero for a number of decision making units (DMUs). As a result, individual stage efficiencies for these DMUs are undefined. We propose a weight assurance region model to restrict ξ₁ and ξ₂, which ensures that both weights are always positive, and therefore individual stage efficiency is always defined. Furthermore, the proposed model is appropriate for policy making in the presence of a priori information about the relative importance of each stage in the overall process. We employ the new model to evaluate the efficiency of secondary education in 65 countries and construct an overall ‘school efficiency’ index. In the first stage we measure the ‘learning environment efficiency’ and in the second we measure the ‘student’s performance efficiency’.