This page contains a list of books that are directly relevant to the discipline of decision analysis and that may be suitable as textbooks in courses related to decision analysis. The list is based on the notes made when searching for a textbook suitable for the class Decision Analysis and Decision Support Systems that Prof. Druzdzel has been teaching at the School of Computing and Information at the University of Pittsburgh. Next to a complete citation to each of the books, the list includes comments directed mainly, but not only, at the suitability of the book as a textbook for a course in decision analysis. The readers should be warned that not only the comments are subjective. The list itself consists of books that we were aware of and that we managed to get a hold of. We will appreciate additions to the list and information whether and where a book is used as a textbook.
Strategic Decision Making Multiobjective Decision Analysis With Spreadsheets
ABSTRACT. Organizations typically have more good ideas for projects than they have resources available to pursue those ideas. Decision analysis can provide practical guidance to the organization on how to get the maximum benefit from those limited resources. This chapter reviews methods for prioritizing projects using mathematical optimization or benefit-cost ratios in concert with standard decision-analysis and risk-analysis tools. These tools include multiattribute utility and value models, decision trees, influence diagrams, and Monte Carlo simulation. To illustrate issues that arise in implementing these approaches in organizations, the use of resource allocation models in hospital capital budgeting is described at length. The chapter concludes with a call for more research on the use of decision analysis in organizational settings.
In their daily lives, people usually weigh multiple criteria implicitly and may be comfortable with the consequences of such decisions that are made based on only intuition.[1] On the other hand, when stakes are high, it is important to properly structure the problem and explicitly evaluate multiple criteria.[2] In making the decision of whether to build a nuclear power plant or not, and where to build it, there are not only very complex issues involving multiple criteria, but there are also multiple parties who are deeply affected by the consequences.
Structuring complex problems well and considering multiple criteria explicitly leads to more informed and better decisions. There have been important advances in this field since the start of the modern multiple-criteria decision-making discipline in the early 1960s. A variety of approaches and methods, many implemented by specialized decision-making software,[3][4] have been developed for their application in an array of disciplines, ranging from politics and business to the environment and energy.[5]
MCDM is concerned with structuring and solving decision and planning problems involving multiple criteria. The purpose is to support decision-makers facing such problems. Typically, there does not exist a unique optimal solution for such problems and it is necessary to use decision-makers' preferences to differentiate between solutions.
The difficulty of the problem originates from the presence of more than one criterion. There is no longer a unique optimal solution to an MCDM problem that can be obtained without incorporating preference information. The concept of an optimal solution is often replaced by the set of nondominated solutions. A solution is called nondominated if it is not possible to improve it in any criterion without sacrificing it in another. Therefore, it makes sense for the decision-maker to choose a solution from the nondominated set. Otherwise, she/he could do better in terms of some or all of the criteria, and not do worse in any of them. Generally, however, the set of nondominated solutions is too large to be presented to the decision-maker for the final choice. Hence we need tools that help the decision-maker focus on the preferred solutions (or alternatives). Normally one has to "tradeoff" certain criteria for others.
The decision space corresponds to the set of possible decisions that are available to us. The criteria values will be consequences of the decisions we make. Hence, we can define a corresponding problem in the decision space. For example, in designing a product, we decide on the design parameters (decision variables) each of which affects the performance measures (criteria) with which we evaluate our product.
(2) Interactive programming: Phases of computation alternate with phases of decision-making (Benayoun et al., 1971;[21] Geoffrion, Dyer and Feinberg, 1972;[22] Zionts and Wallenius, 1976;[23] Korhonen and Wallenius, 1988[24]). No explicit knowledge of the DM's value function is assumed.
In the 1980s, Deng Julong proposed Grey System Theory (GST) and its first multiple-attribute decision-making model, called Deng's Grey relational analysis (GRA) model. Later, the grey systems scholars proposed many GST based methods like Liu Sifeng's Absolute GRA model,[33] Grey Target Decision Making (GTDM)[34] and Grey Absolute Decision Analysis (GADA).[35]
The AHP first decomposes the decision problem into a hierarchy of subproblems. Then the decision-maker evaluates the relative importance of its various elements by pairwise comparisons. The AHP converts these evaluations to numerical values (weights or priorities), which are used to calculate a score for each alternative (Saaty, 1980[36]). A consistency index measures the extent to which the decision-maker has been consistent in her responses. AHP is one of the more controversial techniques listed here, with some researchers in the MCDA community believing it to be flawed.[37][38] The underlying mathematics is also more complicated and requires rational analysis[vague],[38] though it has gained some popularity as a result of commercially available software.
Each year the Operational Support Office of the US National Reconnaissance Office searches for ways to provide better space-reconnaissance information to military and national leaders. We used future value analysis, a combination of three methods to assess future opportunities: (1) a strategic assessment of future opportunities and challenges, (2) a multiple-objective decision analysis using value-focused thinking, and (3) a portfolio analysis using optimization. We then developed a multiple-objective value model to communicate values, evaluate individual tasks, and develop higher value tasks. We used an optimization model to identify the best portfolio of tasks. The office used the models to identify the best tasks for its annual budget in 1998 and, with revisions, in the next two years.
EconPapers FAQ Archive maintainers FAQ Cookies at EconPapers The RePEc blog The RePEc plagiarism page European Journal of Operational Research1977 - 2023Current editor(s): Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo PeccatiFrom ElsevierBibliographic data for series maintained by Catherine Liu (Obfuscate( 'elsevier.com', 'repec' )).Access Statistics for this journal.Track citations for all items by RSS feedIs something missing from the series or not right? See the RePEc data check for the archive and series.Volume 29, issue 3, 1987 The facility layout problem pp. 229-251 Andrew Kusiak and Sunderesh S. Heragu The development of computer software for risk analysis: A decision support system development case study pp. 252-261 P. Clark and C. B. Chapman Project scheduling with resource constraints: A branch and bound approach pp. 262-273 Nicos Christofides, R. Alvarez-Valdes and J. M. Tamarit Optimal production and abatement policies of a firm pp. 274-285 Gustav Feichtinger and Mikulas Luptacik Approximations for operating characteristics in a production-inventory model with variable production rate pp. 286-297 A. G. de Kok Scheduling jobs with release dates and tails on identical machines to minimize the makespan pp. 298-306 Jacques Carlier On the expected value of stochastic linear programs and (dynamic) network flow problems pp. 307-316 Ulrich Fincke and Horst W. Hamacher On a particular quadratic network problem pp. 317-327 Ernesto Queiros Vieira Martins A forward convex-simplex method pp. 328-335 Jonathan D. Stanley A multiple criteria decision analytic approach for evaluating acid rain policy choices pp. 336-352 G. Anandalingam A comparative evaluation of interactive solution methods for multiple objective decision models pp. 353-359 J. T. Buchanan and H. G. Daellenbach Estimating criterion weights using eigenvectors: A comparative study pp. 360-369 E. Takeda, K. O. Cogger and P. L. Yu A fitting algorithm for Markov-modulated poisson processes having two arrival rates pp. 370-377 K. S. Meier-Hellstern A note on the Edmonds-Fukuda pivoting rule for simplex algorithms pp. 378-383 Jens ClausenVolume 29, issue 2, 1987 Editorial pp. 127-383 Jan Schreuder The relationship between decision support systems and operational research: Health care examples pp. 128-134 Duncan Boldy Problem structuring in a hospital pp. 135-143 A. Panayotopoulos and N. Assimakopoulos : An equilibrium model for resource allocation in a health care system pp. 144-158 Louis Delorme and Jean-Marc Rousseau A simulation approach to cost-effectiveness and cost-benefit calculations of screening for the early detection of disease pp. 159-166 J. D. F. Habbema, J. Th. N. Lubbe, G. J. van Oortmarssen and P. J. van der Maas Visual simulation in hospitals: A managerial or a political tool? pp. 167-177 Lyn M. Jones and Andrew J. Hirst Simulation modelling of emergency medical services pp. 178-185 Marek Lubicz and Bożena Mielczarek Register-based description of treatment processes in hospital care pp. 186-191 Sune Vinderslev Petersen Optimal planning of a pediatric semi-intensive care unit via simulation pp. 192-198 Giorgio Romanin-Jacur and Paola Facchin Nursing workload measurement as management information pp. 199-208 Guus de VriesVolume 29, issue 1, 1987 Stochastic models of consumer behaviour pp. 1-23 Udo Wagner and Alfred Taudes On a formalisation of the process of quantitative model building pp. 24-41 Ch. Schneeweiss A comparison of different modelling approaches to strategic energy planning pp. 42-50 Daan Dijk and Matthijs Kok Expert systems in production scheduling pp. 51-59 John J. Kanet and Heimo H. Adelsberger Estimating the lead-time demand distribution when the daily demand is non-normal and autocorrelated Hon-Shiang LAU pp. 60-69 Min-Chiang Wang A deterministic order level inventory model for deteriorating items with two storage facilities pp. 70-73 K. V. S. Sarma Modular product design and product support pp. 74-82 Uday S. Karmarkar and Peter Kubat Optimal resource profiles for program scheduling pp. 83-90 L. Valadares Tavares Reversible-shop scheduling pp. 91-97 I. Adiri, N. Aizikowitz and V. Lev Solving general continuous single facility location problems by cutting planes pp. 98-110 Frank PlastriaVolume 28, issue 3, 1987 Decision and risk analysis pp. 247-260 Herbert Moskowitz and Derek Bunn Exploring and controlling a bank's interest risk: Sensitivity analysis of an asset and liability co-ordination model pp. 261-278 Hermann Meyer zu Selhausen The analysis of a single base in an airlift operation pp. 279-285 Jeya Chandra, Ronald Wasserstein and Arthur Hogan Pricing strategies for a non-replenishable item under variable demand and inflation pp. 286-292 John A. George A dynamic quantity discount lot size model with resales pp. 293-297 Kwon-Ik Sohn and Hark Hwang Economic ordering policy for deteriorating items over an infinite time horizon pp. 298-301 S.K. Goyal The TTT-concept and replacement to extend system life pp. 302-307 Bo Bergman and Bengt Klefsjo Random walk models for search with particular reference to a bounded region pp. 308-320 Brian Conolly and David Roberts On the heterogeneous machine interference with limited server's availability pp. 321-328 Andras Posafalvi and Janos Sztrik An approach for preference ranking of alternatives pp. 329-342 Zahid Y. Khairullah and Stanley Zionts Multiple-use land planning and conflict resolution by multiple objective linear programming pp. 343-350 Fred Glover and Fred Martinson A fuzzy preference relation in the vector maximum problem pp. 351-357 Stefan Chanas and Bronislaw Florkiewicz Activity optimization games with complementarity pp. 358-368 Donald M. Topkis Local decomposition methods for linear programming pp. 369-381 C. van de Panne Facilities layout generalized model solved by n-boundary shortest path heuristics pp. 382-391 J.W. Giffin and L.R. Foulds OR software pp. 392-393 Herve ThiriezVolume 28, issue 2, 1987 Energy models pp. 121-131 Ibrahim Kavrakoglu A DSS design framework for competitive strategy formulation pp. 132-145 Muhittin Oral An application of multi-objective modeling: The case of the Indian sugar industry pp. 146-153 B. Vijayalakshmi A new points system for soccer leagues: Have expectations been realised? pp. 154-157 Abraham Mehrez, Joseph S. Pliskin and Alan Mercer A transient queueing model for Business Office with standby servers pp. 158-174 Stephen K. Mok and Jevaveerasingam Shanthikumar An analysis of advertising and distribution effectiveness pp. 175-179 Sophocles Brissimis and K. E. Kioulafas The application of OR techniques for the prediction and understanding of damages caused by seismic events pp. 180-195 Luciano di Sopr and Giacomo Patrizi A location-allocation problem in a large Belgian brewery pp. 196-206 Ludo F. Gelders, Liliane M. Pintelon and Luk N. Van Wassenhove A large mixed integer production and distribution program pp. 207-217 F. Duran The potential impact of artificial intelligence on the practice of OR pp. 218-225 L. C. Hendry A comment on the article "inspection and maintenance optimization methods" by K.M. Mjelde pp. 226-227 A. Hallefjord, Kurt Jörnsten, S. Storoy and Stein Wallace Multi-input multi-output fuzzy systems and the Inverse Problem pp. 228-230 Costas P. PappisVolume 28, issue 1, 1987 Editorial pp. 1-230 Alan Mercer, Bernhard Tilanus and Hans Zimmermann Editorial to `OR software' pp. 2-230 Herve Thiriez Exact methods for the knapsack problem and its generalizations pp. 3-21 Krzysztof Dudzinski and Stanislaw Walukiewicz Differences in bidding strategies pp. 22-26 Malcolm King and Alan Mercer A model for assessing the work processing capabilities of military command and control systems pp. 27-43 R. G. Coyle Decision making with incomplete information pp. 44-57 Martin Weber Job-shop scheduling with resource-time models of operations pp. 58-73 Jozef Grabowski and Adam Janiak An experimental comparison of several approaches to the discriminant problem with both qualitative and quantitative variables pp. 74-78 Carol A. Markowski and Edward P. Markowski Pruning of decision alternatives in multiple criteria decision making, based on the U method for estimating utilities pp. 79-88 Theodor J. Stewart A note on a pair of nonlinear mixed integer programming problems pp. 89-92 M. S. Mishra, S. Nanda and D. Acharya A non-recursive algorithm for classifying the states of a finite Markov chain pp. 93-95 Howard J. Weiss Infinite horizon Markov decision processes with unknown or variable discount factors pp. 96-100 D. J. White Geometric programming problems with negative degrees of difficulty pp. 101-103 S. B. Sinha, A. Biswas and M. P. Biswal EJOR history and geography in figures pp. 104-107 W. G. M. M. Rutten and C. B. 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