A Case Study in Community Care Using Systems Thinking

This paper uses a recent application of System Dynamics in community care to contribute to a clarification of the role of System Dynamics as a framework for strategic debate. A revised framework for System Dynamics within a philosophy of ‘modelling as learning’ is summarized. This framework is now referred to as Systems Thinking and combines knowledge acquisition and both qualitative and quantitative modelling, supported by microworlds and archetypes to aid dissemination of insights. The emphasis of the paper is on using qualitative models interactively with different groups of participants in the problem domain. The purpose is to assist the development of a shared understanding of how culture, power and politics combine to affect the behaviour of a process, when subjected to externally superimposed changes in responsibility.     

The Effects of Design Changes and Delays on Project Costs

This paper describes a study of a large design and manufacture engineering project, undertaken as part of a Delay and Disruption litigation. Design changes and delays in design approval would have caused delay to the project; in order to fulfil a tight time-constraint, management had to increase parallel development in the network logic, reducing delay but setting up feedback loops that markedly increased total project spend. Cognitive mapping was used to elicit the relationships, which suggested the use of System Dynamics to quantify the effects. Results are described that show the effect of levels of design changes and approval delays, and their compounding effect. The wider implications on modelling projects are also discussed.     

Robust portfolio modeling with incomplete cost information and project interdependencies

Robust portfolio modeling (RPM) [Liesiö, J., Mild, P., Salo, A., 2007. Preference programming for robust portfolio modeling and project selection. European Journal of Operational Research 181, 1488–1505] supports project portfolio selection in the presence of multiple evaluation criteria and incomplete information. In this paper, we extend RPM to account for project interdependencies, incomplete cost information and variable budget levels. These extensions lead to a multi-objective zero-one linear programming problem with interval-valued objective function coefficients for which all non-dominated solutions are determined by a tailored algorithm. The extended RPM framework permits more comprehensive modeling of portfolio problems and provides support for advanced benefit–cost analyses. It retains the key features of RPM by providing robust project and portfolio recommendations and by identifying projects on which further attention should be focused. The extended framework is illustrated with an example on product release planning.     

Systems Dynamics Applications to Industrial and Other Systems

This paper describes the results of ideas derived from the work of the System Dynamics Research Group at the University of Bradford. The basic underlying ideas of System Dynamics are outlined and examples of their application to a number of practical problems given. The major results obtained and the lines of research suggested by these studies are discussed.     

Insuring a risky investment project

In the standard model for insurance demand, the risk is totally exogenous and the insurance premium is paid for out of riskless wealth. This model yields results that are mostly in contradiction to everyday observation and have been used to question the pertinence of expected utility theory on which the model is based. For some years now, several papers have made attempts to provide foundations for a theory of insurance demand that leads to less provocative comparative statics results. In these papers, the risk for which coverage is sought becomes endogenous, and the decision to purchase insurance is made simultaneously with the decision on how much to invest in insurable assets. All these papers use a standard financial investment framework. This paper offers a contribution to this literature by using a slightly different framework: the case of a firm exposed to an insurable risk affecting return on a real investment project. The model is kept simple by using a two-state environment. It yields results that are both more complete and more general than results in previous work with the same motivation.     

Effort estimates through project complexity

This paper reports the results obtained from use of project complexity parameters in modeling effort estimates. It highlights the attention that complexity has recently received in the project management area. After considering that traditional knowledge has consistently proved to be prone to failure when put into practice on actual projects, the paper endorses the belief that there is a need for more open-minded and novel approaches to project management. With a view to providing some insight into the opportunities that integrate complexity concepts into model building offers, we extend the work previously undertaken on the complexity dimension in project management. We do so analyzing the results obtained with classical linear models and artificial neural networks when complexity is considered as another managerial parameter. For that purpose, we have used the International Software Benchmarking Standards Group data set. The results obtained proved the benefits of integrating the complexity of the projects at hand into the models. They also addressed the need of a complex system, such as artificial neural networks, to capture the fine nuances of the complex systems to be modeled, the projects.     

Artificial Intelligence Approaches to Simulation

Recent years have seen a number of attempts to apply both AI methods and AI software tools to the development of both simulations and simulation packages. This paper discusses the motivation behind such work: the increasing need for AI researchers to include simulation in AI systems and use simulation in research, and the need to model intelligent behaviour in OR simulation models. The current research and development effort is reviewed. A system called PROSS (the PROlog Simulation System), constructed to allow the integration of AI methods with traditional discrete simulation, is then briefly presented. It is concluded that AI software tools, and some of the novel approaches to simulation being taken by AI researchers, will have a considerable impact on simulation.     

A fuzzy approach to R&D project portfolio selection

A major advance in the development of project selection tools came with the application of options reasoning in the field of Research and Development (R&D). The options approach to project evaluation seeks to correct the deficiencies of traditional methods of valuation through the recognition that managerial flexibility can bring significant value to projects. Our main concern is how to deal with non-statistical imprecision we encounter when judging or estimating future cash flows. In this paper, we develop a methodology for valuing options on R&D projects, when future cash flows are estimated by trapezoidal fuzzy numbers. In particular, we present a fuzzy mixed integer programming model for the R&D optimal portfolio selection problem, and discuss how our methodology can be used to build decision support tools for optimal R&D project selection in a corporate environment.     

Using system dynamics models with litigation audiences

A litigation process involves many different parties. If models are used to support litigation, then there is a variety of audiences to which the model may be exposed. For example lawyers, members from the plaintiff's and defendant's organisations, expert modellers, arbitrators and judges. This paper discusses the experience of using System Dynamics models to support claims for compensation for time and cost overruns on large and complex projects. In this situation, it is argued that it is vital that the modeller understands how the different audiences will react to the models, otherwise the audience may dismiss the use of the model to support a claim for compensation. This paper discusses the nature of reactions to System Dynamics models by litigation audiences. These reactions highlight issues that the modeller faces when constructing a model. These issues need to be addressed so that the modeller can ensure that the model provides the support required to enable the client to optimise their chances of gaining compensation.     

基于融资能力约束的多模式Max-npv项目调度优化: 双重视角

从项目双方的视角出发,研究融资能力约束下的Max-npv项目调度问题。首先进行问题界定,构建由两个子模型构成的多模式Max-npv项目调度优化模型。随后,鉴于问题的强NP-hard属性,设计针对两个子模型迭代循环求解的禁忌搜索启发式算法,得到项目双方都满意的解。最后用一个实际案例对研究进行验证说明,并分析关键参数对合同双方收益的影响,结果表明:与实际进度安排相比,满意进度安排下合同双方的收益均有显著的提升;承包商和业主的融资能力、项目截止日期、承包商收益底线、折现率及支付比例均会对双方的收益产生重要影响。     

The effect of human agent in project management

The article deals with the effect of a human agent on the activity realization in a project. It does so from the perspective of the Theory of Constraints where the weakest point is the deadline of partial activity. Every existing activity in any project is, to a higher or lower extent, determined by the effect of the human agent. The inefficiency of a number of projects in practice is largely caused by an unsuccessful realization of partial activities. The effect of the human agent is in this respect fundamental. The human agent, as an allocated resource in the activity, is liable to a number of non-specified impacts and stimuli, and as such s/he is rather versatile in his/her behaviour. The versatility of the human agent in projects can be described by the “Student Syndrome” phenomenon and by the first “Parkinson’s law”. Both these qualitative phenomena create a starting point for the introduced theoretical and quantitative research. The findings in this article are based on the set of real data of work effort of the students of daily study programme on one university in the Czech Republic. The article presents, as the authors’ own theoretical contribution, a mathematical model for the “Student Syndrome” phenomenon with a practical use in quantitative methods of project management. This model was derived analytically from a performed data analysis and we can assume that it will be useful for further theoretical development of quantitative methods in project management. In the article we deduce the theoretical differentiation of the “Student Syndrome” phenomenon in work effort into three terminable phases during three different types of resource work allocation. We can regard this original viewpoint as suggestive for the area of human resources management in projects. Its contribution lies in delimitation of time-targeted resource stimulation, which may lead to lower project costs, besides higher work efficiency and compliance with time-targeted deadlines of activity termination. The article brings the quantification of qualitative features of the human agent in project management.     

Cost impact of float loss on a project with adjustable activity durations

Although delays to non-critical activities within the float do not always affect the overall completion time of a project, they commonly cause disputes over the impact cost and apportionment resulting from the complexity of resource utilization in construction projects. Therefore, considerable attention has been focused on providing an effective and reliable method for analysing the effects of float loss. Several recent studies have proposed various methods; however, most of these methods are based on the assumption of a fixed duration for each activity or activity-based cost simulation. Few studies have considered the trade-off between time and costs and the integration of project resources. Using genetic algorithms, this study introduces a critical path method (CPM)-modified resource-integrated optimization model and successfully quantifies the impact of float loss on the total cost of the project. The results provide objective quantification for accurately evaluating the impact of within-float delays and facilitate the analysis of the impact of delay claims on cost and apportionment in construction projects.     

Using quantile regression for rate-making

Regression models are popular tools for rate-making in the framework of heterogeneous insurance portfolios; however, the traditional regression methods have some disadvantages particularly their sensitivity to the assumptions which significantly restrict the area of their applications. This paper is devoted to an alternative approach–quantile regression. It is free of some disadvantages of the traditional models. The quality of estimators for the approach described is approximately the same as or sometimes better than that for the traditional regression methods. Moreover, the quantile regression is consistent with the idea of using the distribution quantile for rate-making. This paper provides detailed comparisons between the approaches and it gives the practical example of using the new methodology.     

Tools for resource-constrained project scheduling and control: forward and backward slack analysis

Project managers generally consider slack as a measure of the scheduling flexibility associated with the activities in the project network. Nevertheless, when resource constraints appear, this information must be calculated and analysed carefully. In this context, to handle project feasible schedules is very hard work for project managers. In order to develop useful tools for decision making, the authors extend the concepts of activity slack and define a new activity criticality index based on them that permits us to classify the activities in the resource-constrained project scheduling and control context. Additionally, these new concepts have been integrated into standard project management software as new commands. Hence the capabilities of project management software are improved. Finally, an example that illustrates the use and application of the new activity classification is also included.     

The virtual design team: A computational model of project organizations

Large scale and multidisciplinary engineering projects (e.g., design of a hospital building) are often complex. They usually involve many interdependent activities and require intensive coordination among actors (i.e., designers) to deal with activity interdependencies. To make such projects more effective and efficient, one needs to understand how coordination requirements are generated and what coordination mechanisms should be applied for given project situations. Our research on the Virtual Design Team (VDT) attempts to develop a computational model of project organizations to analyze how activity interdependencies raise coordination needs and how organization design and communication tools change team coordination capacity and project performance. The VDT model is built based on contingency theory (Galbraith, 1977) and our observations about collaborative and multidisciplinary work in large, complex projects. VDT explicitly models actors, activities, communication tools and organizations. Based on our extended information-processing view of organizations, VDT simulates the actions of, and interactions among actors as processes of attention allocation, capacity allocation, and communication. VDT evaluates organization performance by measuring emergent project duration, direct cost, and coordination quality. The VDT model has been tested internally, and evaluated externally through case-studies. We found three way qualitative consistency among predictions of the simulation model, of organization theory, and of experienced project managers. In this paper, we present the VDT model in detail and discuss some general issues involved in computational organization modeling, including level of abstraction of tasks and actors' reasoning, and model validation.     

An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis

The application of multi objective evolutionary algorithms (MOEA) in the design optimisation of microelectromechanical systems (MEMS) is of particular interest in this research. MOEA is a class of soft computing techniques of biologically inspired stochastic algorithms, which have proved to outperform their conventional counterparts in many design optimisation tasks. MEMS designers can utilise a variety of multi-disciplinary design tools that explore a complex design search space, however, still follow the traditional trial and error approaches. The paper proposes a novel framework, which couples both modelling and analysis tools to the most referenced MOEAs (NSGA-II and MOGA-II). The framework is validated and evaluated through a number of case studies of increasing complexity. The research presented in this paper unprecedentedly attempts to compare the performances of the mentioned algorithms in the application domain. The comparative study shows significant insights into the behaviour of both of the algorithms in the design optimisation of MEMS. The paper provides extended discussions and analysis of the results showing, overall, that MOGA-II outperforms NSGA-II, for the selected case studies.     

Facilitated modelling in operational research

The traditional way of employing operational research in organisational interventions has been the expert mode. In this mode, the problem situation faced by the client is given to the operational research consultant, who then builds a model of the situation, solves the model to arrive at an optimal (or quasi-optimal) solution, and then provides a recommendation to the client based on the obtained solution. An alternative mode of engagement is to conduct the whole intervention together with the client: from structuring and defining the nature of the problem situation of interest, to supporting the evaluation of priorities and development of plans for subsequent implementation. In this latter mode, the operational researcher works throughout the intervention not only as an analyst, but also as a facilitator to the client. This paper discusses this latter mode of engagement with clients, with particular emphasis on the use of facilitated modelling as the intervention tool. Drawing on research scattered across a range of publications and domains, the review presented here provides a formal definition of facilitated modelling, together with a general framework that allows the conceptualisation of a wide variety of facilitated modelling approaches to organisational intervention. Design issues in facilitated modelling and their practical implication are discussed, and directions for future research identified.     

Tropical optimization problems in time-constrained project scheduling

We consider a project that consists of activities to be performed in parallel under various temporal constraints, which include start-start, start-finish and finish-start precedence relationships, release times, deadlines and due dates. Scheduling problems are formulated to find optimal schedules for the project with respect to different objective functions to be minimized, such as the project makespan, the maximum deviation from the due dates, the maximum flow-time and the maximum deviation of finish times. We represent these problems as optimization problems in terms of tropical mathematics, and then solve them by applying direct solution methods of tropical optimization. As a result, new direct solutions of the scheduling problems are obtained in a compact vector form, which is ready for further analysis and practical implementation. The solutions are illustrated by simple numerical examples.     

Une methode de gradient conjugue sur des varietes application a certains problemes de valeurs propres non lineaires

Minimization of a functional under equality constraints is viewed as a particular case of minimization over a manifold. Using tools from Differential Geometry we formulate a Conjugate Gradient method and prove its convergence. The global behaviour of the algorithm is also studied. From these “idealized” algorithms working on a manifold, we then deduce practical methods with comparable convergence rates. We have used these methods to solve “Nonlinear eigenvalue problems” numerically.