Optimizing anti-terrorism resource allocation

Since spring of 2002 we have been working on a methodology, decision model, and cognitive support system to aid with effective allocation of anti-terrorism (AT) resources at Marine Corps installations. The work has so far been focused on the military domain, but the model and the software tools developed to implement it are generalizable to a range of commercial and public-sector settings including industrial parks, corporate campuses, and civic facilities. The approach suggests that anti-terrorism decision makers determine mitigation project allocations using measures of facility priority and mitigation project utility as inputs to the allocation algorithm. The three-part hybrid resource allocation model presented here uses multi-criteria decision-making techniques to assess facility (e.g., building, hangar) priorities, a utility function to calculate anti-terrorism project mitigation values (e.g., protective glazing, wall coatings, and stand-off barriers) and optimization techniques to determine resource allocations across multiple, competing AT mitigation projects. The model has been realized in a cognitive support system developed as a set of loosely coupled Web services. The approach, model, and cognitive support system have been evaluated using the cognitive walkthrough method with prospective system users in the field. In this paper we describe the domain, the problem space, the decision model, the cognitive support system and summary results of early model and system evaluations.

[1]  W. Edwards.  How to Use Multi-Attribute Utility Measurement for Social Decision Making , 1976 .

[2]  Cathleen Wharton,et al.  The cognitive walkthrough method: a practitioner's guide , 1994 .

[3]  T Au,et al.  ENGINEERING ECONOMICS FOR CAPITAL INVESTMENT ANALYSIS :(2ND ED. ) , 1992 .

[4]  David Otley,et al.  Performance Management: A Framework for Management Control Systems Research , 1999 .

[5]  Norman P. Archer,et al.  Project portfolio selection through decision support , 2000, Decis. Support Syst..

[6]  J. Wallenius,et al.  Using qualitative data in multiple objective linear programming , 1990 .

[7]  Deborah L Thurston,et al.  A formal method for subjective design evaluation with multiple attributes , 1991 .

[8]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[9]  H. Simon,et al.  Models of Man. , 1957 .

[10]  Jakob Nielsen,et al.  Usability inspection methods , 1994, CHI 95 Conference Companion.

[11]  John M. Carroll,et al.  Making Use: Scenario-Based Design of Human-Computer Interactions , 2000 .

[12]  Kristina Höök,et al.  Using cognitive walkthrough for evaluating a CSCW application , 1994, CHI Conference Companion.

[13]  Piet Rietveld,et al.  The value of statistical life in road safety: a meta-analysis. , 2003, Accident; analysis and prevention.

[14]  Mary Beth Rosson,et al.  Getting around the task-artifact cycle: how to make claims and design by scenario , 1992, TOIS.

[15]  John Millar Carroll.  The Nurnberg Funnel: Designing Minimalist Instruction for Practical Computer Skill , 1990 .

[16]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[17]  John R. Canada,et al.  Past and Present Methods of Manufacturing Investment Evaluation: A Review of the Empirical and Theoretical Literature , 1992 .

[18]  Roger N. Wabalickis.  Justification of FMS with the analytic hierarchy process , 1988 .

[19]  George J. Kyparisis,et al.  Project selection with discounted returns and multiple constraints , 1996 .

[20]  竹内 憲司.  A meta-analysis of the value of statistical life , 2000 .

[21]  O. Svenson,et al.  Decision making : cognitive models and explanations , 1997 .

[22]  Cathleen Wharton,et al.  Cognitive Walkthroughs: A Method for Theory-Based Evaluation of User Interfaces , 1992, Int. J. Man Mach. Stud..

[23]  Jonathan F. Bard,et al.  An interactive approach to R&D project selection and termination , 1988 .

[24]  Herbert A. Simon,et al.  The new science of management decision , 1960 .

[25]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[26]  R. Ranyard,et al.  Cognitive process models and explanations of decision making , 2002 .

[27]  A. D. Henriksen,et al.  A practical R&D project-selection scoring tool , 1999 .

[28]  Michael J. Kahn,et al.  Formal usability inspections , 1994 .

[29]  G. Barbarosoglu,et al.  CAPITAL RATIONING IN THE PUBLIC SECTOR USING THE ANALYTIC HIERARCHY PROCESS , 1995 .

[30]  Efraim Turban,et al.  Integrating Expert Systems and Decision Support Systems , 1986, MIS Q..

[31]  R. Ramanathan,et al.  Using AHP for resource allocation problems , 1995 .

[32]  Hemant K. Bhargava,et al.  Beyond Spreadsheets: Tools for Building Decision Support Systems , 1999, Computer.

[33]  John W. Fowler,et al.  A hybrid approach using the analytic hierarchy process and integer programming to screen weapon systems projects , 2003, IEEE Trans. Engineering Management.

[34]  Ward Edwards,et al.  How to Use Multiattribute Utility Measurement for Social Decisionmaking , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[35]  Ralph H. Sprague,et al.  Building Effective Decision Support Systems , 1982 .

[36]  Matthew J. Liberatore,et al.  An extension of the analytic hierarchy process for industrial R&D project selection and resource allocation , 1987, IEEE Transactions on Engineering Management.

[37]  CAROLINE PARKER.  An approach to requirements analysis for decision support systems , 2001, Int. J. Hum. Comput. Stud..

[38]  Gary Klein,et al.  Sources of Power: How People Make Decisions , 2017 .