Formulating and solving sequential decision analysis models with continuous variables

  title={Formulating and solving sequential decision analysis models with continuous variables},
  author={Jeffrey S. Stonebraker and Craig W. Kirkwood},
  journal={IEEE Transactions on Engineering Management},
This paper presents a new decision analysis approach for modeling decision problems with continuous decision and/or random variables, and applies the approach to a research and development (R&D) planning problem. The approach allows for compact, natural formulation for classes of decision problems that are less appropriately addressed with standard discrete-variable decision analysis methods. Thus it provides a useful alternative analysis approach for problems that are often addressed in… 
Solving a Multicriteria Decision Tree Problem Using Interactive Approach
A new technique for a dynamic multicriteria decision-making problem under risk using a decision tree and interactive approach is proposed and a real-world example is presented to show applicability of the procedure.
Multi-criteria Decision Aiding in Project Planning Using Decision Trees and Simulation
The aim of the paper is to present a simple, yet comprehensive, methodology for project planning that permits the consideration of both multiple criteria and risk, and combines decision trees, simulation modelling and stochastic dominance rules.
Modeling Pilot s Sequential Maneuvering Decisions by a Multistage Influence Diagram
The paper presents an approach toward the off-line computation of preference optimal flight paths against given air combat maneuvers. The approach consists of a multistage influence diagram modeling
Multicriteria decision aiding in project planning using dynamic programming and simulation
The concept of “project planning” is not uniformly understood. Some authors reduce it to scheduling – determining the dates for performing schedule activities and deadlines for reaching milestones.
Analysis of the Sensitivity of Decision Analysis Results to Errors and Simplifications in Problem Structure: Application to Lake Erie Ecosystem Management
Results show that spline-based solutions often yield potentially superior decisions from those based on discretized decision spaces, but that omitting important uncertainties makes more of a difference in this case study's decisions and indexes than simplifying the decision space.
Response surface approximation in Bayesian decision analysis using a multidimensional cubic spline: application to Lake Erie ecosystem management
  • Jong Bum Kim, B. Hobbs, J. Koonce
  • Business
    SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483)
  • 2003
This study proposes a multidimensional cubic spline for interpolating the performance of alternatives between a few simulated points and shows that spline-based solutions often yield potentially superior decisions from those based on discretized-decision spaces.
Programmatic Risk Analysis for Critical Engineering Systems Under Tight Resource Constraints
The Advanced Programmatic Risk Analysis and Management model (APRAM), a decision-support framework for the management of the risk of failures of dependent engineering projects within programs, is described.


An algebraic approach to formulating and solving large models for sequential decisions under uncertainty
This article presents an algebraic approach to formulating and solving large models for sequential decisions under uncertainty. With this approach, decision analysis optimization methods can be
Representation and solution of decision problems using sequential decision diagrams
It is shown that a unified framework consisting of a sequential diagram, an influence diagram, and a common formulation table for the problem's data, suffices for compact and consistent representation, economical formulation, and efficient solution of (asymmetric) decision problems.
Strategic planning for investment in R&D using decision analysis and mathematical programming
This paper investigates the strategic planning and investments associated with research and development (R&D) project selection and budgeting within a division of an aerospace firm. A model is
Optimal Discrete Approximations for Continuous Outcomes with Applications in Decision and Risk Analysis
In decision and risk analysis, it is common to use discrete probability distributions to approximate uncertain events with continuous outcomes. This paper discusses how these approximations may be
Valuation-Based Systems for Bayesian Decision Analysis
A new method for representing and solving Bayesian decision problems is proposed, called a valuation-based system and has some similarities to influence diagrams, but unlike influence diagrams which emphasize conditional independence among random variables, valuation- based systems emphasize factorizations of joint probability distributions.
Evaluating Influence Diagrams
An algorithm is developed that can evaluate any well-formed influence diagram and determine the optimal policy for its decisions and can be performed using the decision maker's perspective on the problem.
Analytical Effectiveness of Mathematical Models for R&D Project Selection
Four mathematical programming models for R&D project selection and funding are developed, based on similar models and results in the literature. Project selection and funding decision planning data
R&D Project Selection and Manpower Allocation with Integer Nonlinear Goal Programming
A non-linear integer goal programming model is described via a case example that selects projects and allocates researchers to projects such that a prioritized goal structure is most satisfactorily achieved.
Implementing an Algorithm to Solve Large Sequential Decision Analysis Models
  • C. Kirkwood
  • Computer Science
    IEEE Trans. Syst. Man Cybern. Syst.
  • 1994
An implementation is presented of an algorithm to solve large sequential decision analysis models in the Pascal programming language that requires only a modest personal computer to quickly solve decision trees with several hundred thousand endpoints.
A Dynamic Programming Approach to R and D Budgeting and Project Selection
  • S. W. Hess
  • Economics
    IRE Transactions on Engineering Management
  • 1962
Contemporary models of research and development are incomplete in that they ignore the many reappraisals and budgeting decisions that occur in the time between a project's proposal and its