A model and approach to the challenge posed by optimal power systems planning

Currently, there is a need to plan and analyze the electric power transmission system in greater detail and over larger geographic areas. Existing models approach the problem from different perspectives. Each model addresses different aspects of and has different approximations to the optimal planning process. In order to scope out the huge challenge of optimal transmission planning, this paper presents a new modeling approach for inter-regional planning and investment in a competitive environment. This modeling approach incorporates the detailed generator, topology and operational aspects found in production cost planning models into a larger framework that can find optimal sets of transmission expansion projects. The framework proposed here can be used in an auction to award investment contracts or as a part of a more general policy analysis. The solution yields the set of transmission projects that have the highest expected benefits, while also representing generic generation expansions under the same objective. The model is a two-stage, mixed-integer, multi-period, N-1-reliable model with investment, unit commitment, and transmission switching. The combination of combinatorial, stochastic and operational elements means this model may be computationally intractable without judicious modelling aggregations or approximations to reduce its size and complexity. Nevertheless we show via a dual problem that analysing the economics and sensitivity of the solution is computationally more straightforward.     

Methodology for participatory policy analysis

In the course of time it has become clear that policy analysts who use traditional formal modeling techniques have limited impact on policy making regarding complex policy problems. These kinds of problems require the analyst to combine scientific insights with subjective knowledge resources and to improve communication between the parties involved in the policy problem. A policy analyst who takes into account the need for social interaction has different participatory methods at his disposal, such as gaming/simulations, consensus conferences, and electronic meetings. Some assumptions with regard to the theoretical base, the application, and the effectiveness of participatory methods are formulated in this article. These assumptions can be tested and supplemented by means of comparative research on the effectiveness of participatory methods in different policy situations.     

Computational adequacy for recursive types in models of intuitionistic set theory

This paper provides a unifying axiomatic account of the interpretation of recursive types that incorporates both domain-theoretic and realizability models as concrete instances. Our approach is to view such models as full subcategories of categorical models of intuitionistic set theory. It is shown that the existence of solutions to recursive domain equations depends upon the strength of the set theory. We observe that the internal set theory of an elementary topos is not strong enough to guarantee their existence. In contrast, as our first main result, we establish that solutions to recursive domain equations do exist when the category of sets is a model of full intuitionistic Zermelo–Fraenkel set theory. We then apply this result to obtain a denotational interpretation of FPC, a recursively typed lambda-calculus with call-by-value operational semantics. By exploiting the intuitionistic logic of the ambient model of intuitionistic set theory, we analyse the relationship between operational and denotational semantics. We first prove an “internal” computational adequacy theorem: the model always believes that the operational and denotational notions of termination agree. This allows us to identify, as our second main result, a necessary and sufficient condition for genuine “external” computational adequacy to hold, i.e. for the operational and denotational notions of termination to coincide in the real world. The condition is formulated as a simple property of the internal logic, related to the logical notion of 1-consistency. We provide useful sufficient conditions for establishing that the logical property holds in practice. Finally, we outline how the methods of the paper may be applied to concrete models of FPC. In doing so, we obtain computational adequacy results for an extensive range of realizability and domain-theoretic models.     

Policy analytics need more than a spreadsheet: a case study in funding formulae

This article presents two case studies, concerning the allocation of £Billions by a mechanism communicated via spreadsheet models. It argues that technical analytic skills as well as policy development skills are a vital component of governance. In the UK, Central Government uses funding formulae to distribute money to local service providers. One commonly stated goal of such formulae is equity of service provision. However, given the complexity of public services, together with variations in need, delivery style and the exercise of stakeholder judgement as to which needs should be met and how, such formulae frequently obscure the process by which equity has been taken into account. One policy ‘solution’ to managing such tensions is to seek ‘transparency’. With respect to funding formulae, this commonly involves publishing the underlying data and formulae in spreadsheets. This paper extends the argument that such ‘transparency’ requires an audience that understands the policy assumptions (and related conceptualisations), data sources, methodological approaches and interpretation of results. It demonstrates how the search for policy ‘transparency’ is also met by the technical quality assurance goals that the operational research community would recognise as best practice in the development both of software generally and spreadsheet models specifically. Illustrative examples of complex formulae acting to subvert equity are drawn from the English Fire and Rescue Service and Police Service allocation formulae. In the former, an increase in the amount of deprivation, as measured by one of six indicators, has the perverse effect of decreasing the financial allocation. In the latter, metropolitan areas such as London are found to gain most from the inclusion of variables measuring sparsity. The conclusion from these scenarios is that the steps needed to for technical quality assurance and policy transparency are mutually reinforcing goals, with policy analysts urged to make greater use of technical analytic skills in software development.     

Modeling safety culture as a socially emergent phenomenon: a case study in aircraft maintenance

Safety culture is often understood as encompassing organizational members’ shared attitudes, beliefs, perceptions and values associated with safety. Safety culture theory development is fraught with inconsistencies and superficiality of measurement methods, because the dynamic and political nature of culture is often ignored. Traditionally, safety culture is analyzed by survey-based approaches. In this paper we propose a novel, systemic, interdisciplinary approach for investigating safety culture that combines multi-agent system modeling with organizational ethnography. By using this approach, mechanisms of emergence of safety culture from daily practices, operations and interactions of organizational actors can be modeled and analyzed. The approach is illustrated by a case study from the aircraft maintenance domain, based on existing ethnographic data. Using the proposed approach we were able to reproduce and explain emergent characteristic patterns of commitment to safety in the maintenance organization from this study. The model can be used for theory development and as a management tool to evaluate non-linear impacts of organizational arrangements on workers’ commitment to safety.     

IPSSIS: An integrated multicriteria decision support system for equity portfolio construction and selection

A fundamental principle of modern portfolio theory is that comparisons between portfolios are generally made using two criteria, corresponding to the first two moments of return distributions, namely the expected return and portfolio variance. According to this model and according to most of the portfolio models derived from the stochastic dominance approach, the group of portfolios open to comparisons is divided into two parts: on the one hand there are the efficient portfolios (those that are not dominated by any other portfolio in the group), and on the other, those that are dominated. In other words, these models do not solve for one optimal portfolio, but rather solve for an efficient set of portfolios, among which the investor must choose, given his preference system. One criticism over these models, which has often been addressed both by practitioners and academics, is that they fail to embody the objectives of the decision maker (DM), through the various stages of the decision process. Our purpose in this article is to present an integrated and innovative methodological approach for the construction and selection of equity portfolios, which will take into account the inherent multidimensional nature of the problem, while allowing the DM to incorporate his preferences in the decision process. The proposed approach, which grounds its basis on the field of multiple criteria decision making (MCDM) and more specifically on multiobjective mathematical programming (MMP), is implemented in the IPSSIS (Integrated Portfolio Synthesis and Selection Information System) decision support system (DSS). The validity of the proposed approach is tested through an illustrative application in the Athens Stock Exchange (ASE).     

Energy policy modelling in developing and industrializing countries

A large number of models have been developed and used for energy policy planning, in a regional, national or international level, in order to cope with the broad variety of issues related to the energy problem. Energy models belong to the class of policy models, which address fuzzy and complex issues involving many non-quantitative factors, such as political issues, behavioural aspects, etc., as well as many uncertainties and lack of rigorous knowledge concerning the structure of the reference system, and the interrelationships of its elements. The role of energy policy models is very important, since they enhance understanding and communication, and they assist the policymakers to review plausible future configurations of relevant decision variables and parameters. In this paper one of the most important areas of energy modelling is investigated, that concerning the interactions between energy and economy in the group of Developing and Industrializing Countries (DIC's). It is pointed out that energy models used in the DIC's must capture the particular features of energy policy in these countries, such as rapid economic development fueled by expensive, depleting and often imported energy resources; dependence on foreign resources such as energy, capital, technology, etc.; management of indigenous resources, social structural changes, rapid population growth, urbanization and industrialization. In order to improve energy models and enhance their contributions in policy analysis, it is proposed that modelling efforts should be directed towards a better understanding of the energy-economy relationships in the DIC's, as well as towards the development of validated data bases.     

Some mathematical aspects of the political business cycle

Under the hypothesis of a myopic electorate, vote-loss-minimizing behavior by the party in power, subject to a dynamic inflation-unemployment relation, is shown to generate an attractive, stable electoral policy cycle. The model presented is derived, with some improvements, from the analogous models of MacRae and Nordhaus. Furthermore, an attempt is made to specify the mathematical aspects of the problem by the Poincaré mapping.This work was realized within the activities of CNR, Gruppo Nazionale Analisi Funzionale (GNAFA). The author wishes to thank Professor M. D. Intriligator for his many comments, suggestions, and critique.     

Formulations for a problem of petroleum transportation

Oil tankers play a fundamental role in every offshore petroleum supply chain and due to its high price, it is essential to optimize its use. Since this optimization requires handling detailed operational aspects, complete optimization models are typically intractable. Thus, a usual approach is to solve a tactical level model prior to optimize the operational details. In this case, it is desirable that tactical models are as precise as possible to avoid too severe adjustments in the next optimization level. In this paper, we study tactical models for a crude oil transportation problem by tankers. We did our work on the top of a previous paper found in the literature. The previous model considers inventory capacities and discrete lot sizes to be transported, aiming to meet given demands over a finite time horizon. We compare several formulations for this model using 50 instances from the literature and proposing 25 new harder ones. A column generation-based heuristic is also proposed to find good feasible solutions with less computational burden than the heuristics of the commercial solver used.     

Management Adopts Operational Research: Session Report

Quantitative methods are derived to assist buyers purchasing commodities in fluctuating price markets. Demand is known whilst price is a stochastic variable which may contain trends or seasonal fluctuations. The essential feature of the problem is that the buyer has many opportunities to make a purchase.Mathematical models are formulated to describe particular commodity buying problems. The optimal purchasing policy is derived by using dynamic programming. It consists of a set of discrete price breaks at each buying opportunity together with the associated stock levels the buyer should aim to achieve at each price break with his purchase at this opportunity. The price breaks are dependent on the probability density functions of future prices and the number of future buying opportunities. Recurrence relations are derived to calculate these price breaks. The case of restrictions on the purchase quantity at each price offer, either because of supply limitations or by the buyer as a policy decision, and price discounts are also considered.A case study illustrating the techniques is given and the methods are extended to purchasing for a blending problem with substitutable commodities.     

Optimal Short Horizon Distribution Operations in Reusable Container Systems

Manufacturers in many countries are facing increasing market pressures to use returnable containers. Few studies address the day-to-day operational problems of controlling production and distribution that are inherent in closed systems that reuse containers. In this paper we present a formulation of an optimal configuration of this type of system. In particular, we model the reusable bottle production and distribution activities of a large soft drink manufacturer located in Mexico City, Mexico. Two types of operational research models are combined to form the overall optimization system. A pair of linear programs (one aggregated, the other disaggregated) determines a master plan that is subsequently fined-tuned on a shift-by-shift basis using a difference equation simulation model. The simulation model mimics the heuristic ‘rules of thumb’ used by production planners for product distribution and container reuse planning. The results of our study indicate that this formulation provides a timely response in the field to key operational problems addressed by no previous approach. Included are better organizational control (through providing one-week production and distribution plans), feedback allowing modification of heuristic rules previously used in controlling the distribution of product and container reuse, and improvement in inventory behaviour such as avoiding shortages. These improvements have resulted in considerable market share gains since the models were implemented.     

Predictive analysis of concealed social network activities based on communication technology choices: early-warning detection of attack signals from terrorist organizations

Terrorist threat prevention and counteraction require timely detection of hostile plans. However, adversary efforts at concealment and other challenges involved in monitoring terrorist organizations may impede timely intelligence acquisition or interpretation. This study develops an approach to analyzing technological means rather than content of communications produced within the social networks comprising covert organizations, and shows how it can be applied towards detecting terrorist attack precursors. We find that differential usage patterns of hi-tech versus low-tech communication solutions could reveal significant information about organizational activities, which may be further used to detect signals of impending terrorist attacks. (Such potential practical utility of our method is supported by the detailed empirical analysis of available al Qaeda communications.) The described approach thus provides a common framework for utilizing diverse activity records from heterogeneous sources as well as contributes new tools for their rapid analysis aimed at better informing operational and policy decision-making.     

The Blackett Memorial Lecture: 3rd December 1998

This paper analyses Patrick Blackett's role as an adviser on science and technology policy to the Labour Party in the 1950s and 1960s. It highlights his advocacy of an interventionist stance on the part of government by reference to his belief that British industrial performance was being affected adversely by a misallocation of R&D resources in favour of the military-defence sector at the expense of civilian manufacturing industry. This serves as a prelude to an appraisal of Blackett's career as an official adviser on industrial policy to the Labour Governments in office between 1964 and 1970. During that time Blackett fulfilled key roles in the formation of the new Ministry of Technology and the Industrial Reorganisation Corporation. The overall conclusion is that despite Blackett's dual status as the ‘father of OR’ and the leading scientist of the left, his effectiveness was limited by a naïve belief in the relevance of a policy stance validated by reference to his experiences in operational research during the Second World War. It was simply not possible to replicate in a peacetime economy, subject to democratic checks and balances, the extreme centralised control characteristic of total war.     

Rational modelling in understanding and aiding human decision-making: About two case studies

The last few years have brought a large movement of interrogating issues concerning the role and image of Operations Research. But, as a matter of paradox, the ‘OR crisis’ gives a better understanding of the role of rational modelling in choice processes and decision making. Rational models are a mean for conceiving idealised behaviour—rational myths—in structured situations; they are not first of all destined to be implemented or applied; they are the reference against which the analyst confronts the observed behaviour of specified actors.This confrontation permits the analyst to build with these actors a new vision of the constraints and objectives in which they operate. The resulting organisational dynamics are the soundest basis for evaluating the efficiency of this process.It is argued that the underlying mechanism of this learning process can be generally specified as a ‘tool-structure interaction’. These concepts describe a possible bridge between OR and organizational studies; it may lead to a renewed research in Management Science, avoiding the known pitfalls of these fields, when considerated separately in practice or in training.These points will be illustrated by the help of two cases studies concerning respectively scheduling problems in a job-shop and risky decisions in oil production investments.     

Valuating residential real estate using parametric programming

When the estimation of the single equation multiple linear regression model is looked upon as an optimization problem, we show how the principles and methods of optimization can assist the analyst in finding an attractive prediction model. We illustrate this with the estimation of a linear prediction model for valuating residential property using regression quantiles. We make use of the linear parametric programming formulation to obtain the family of regression quantile models associated with a data set. We use the principle of dominance to reduce the number of models for consideration in the search for the most preferred property valuation model (s). We also provide useful displays that assist the analyst and the decision maker in selecting the final model (s). The approach is an interface between data analysis and operations research.     

Simulating organizational decision making in a regulated industry

This paper presents models that simulate executive decision making in the electric utility industry. One is derived from interviews in the Southern California electric utility industry. The other is created to address the questionable theoretical aspects of the executive based model. Each is tested with econometric statistical procedures, and conclusions are derived from a comparative analysis of the results. The results are then used to derive policy implications for the electric utility firm and the regulatory body.     

Modeling operational risk incorporating reputation risk: An integrated analysis for financial firms

It has been shown in the empirical literature that operational losses of financial firms can cause severe reputational losses, which, however, are typically not taken into account when modeling and assessing operational risk. The aim of this paper is to fill this gap by assessing the consequences of operational risk for a financial firm including reputational losses. Toward this end, we extend current operational risk models by incorporating reputation losses. We propose three different models for reputation risk: a simple deterministic approach, a stochastic model using distributional assumptions, and an extension of the second model by taking into account a firm’s ability to deal with reputation events. Our results emphasize that reputational losses can by far exceed the original operational loss and that neglecting reputational losses may lead to a severe underestimation of certain operational risk types and especially fraud events.     

On Markovian approximations for virtual-build-to-order systems

The Virtual Build-to-Order (VBTO) approach strives to allow a producer to fulfil customers with the specific product variants they seek more efficiently than a conventional order fulfilment system. It does so by opening the planning pipeline. Here the feasibility of modelling the VBTO system as a Markov process is investigated. Two system configurations are considered—a random pipeline feed policy that assumes only knowledge of the overall demand pattern and an informed policy that ensures a mix of different variants in the system. First-order Markov models, which assume stationarity requirements are satisfied, are developed for small VBTO systems. The model for the informed feed policy has excellent agreement with simulation results and confirms the superiority of this policy over the random policy. The model for the random policy is more accurate at high variety than at low variety levels. Accuracy is improved with a second-order Markov model. Although impractical for modelling large scale VBTO systems for either configuration, the Markov approach is valuable in providing insights, theoretical foundations and validation for simulation models. It aids the interpretation of observations from simulations of large scale systems and explains the mechanism by which an unrepresentative stock mix develops over time for the random policy.     

Applied general equilibrium modeling for environmental policy analysis

Incorporating environmental regulation and its impact in general equilibrium models has by now a twenty years long tradition. In 1970, Leontief extended his input-output approach to quantify environmental repercussions on the economic structure. The shortcomings of this model, such as fixed coefficients in technological processes or zero price and income elasticities of demand, can be resolved by using a quantitative general equilibrium model. The objective of this paper is to employ such a model to quantify the economic effects of environmental policy and to present a cost-effectiveness analysis of different market instruments in environmental policy.