Binary decision diagrams for generating and storing non-dominated project portfolios with interval-valued project scores

When selecting a portfolio (i.e., set of) projects, the projects are often evaluated by additive scores with respect to multiple attributes. Uncertainty or incomplete information about projects’ scores can be modeled with plausible lower and upper bounds on the projects’ scores. It is recommended to select a non-dominated (ND) portfolio, that is a portfolio such that it is not possible to select another portfolio which has (i) at least as high value with respect to every attribute for all plausible scores, (ii) and has strictly higher value with respect to at least one attribute for some plausible scores. In this paper, we lay a foundation on computing (ND) project portfolios. We also present an algorithm based on binary decision diagrams (BDDs) for generating the ND portfolios. We show that our algorithms can provide significant computational advantages over previous algorithms. We also explore how BDDs can be used for storing large numbers of ND portfolios and how such BDDs can be efficiently generated.

[1]  Juuso Liesiö,et al.  Adjustable robustness for multi-attribute project portfolio selection , 2016, Eur. J. Oper. Res..

[2]  David Bergman,et al.  Discrete Optimization with Decision Diagrams , 2016, INFORMS J. Comput..

[3]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Matthias Ehrgott,et al.  Minmax robustness for multi-objective optimization problems , 2014, Eur. J. Oper. Res..

[5]  Ralph L. Keeney,et al.  Decisions with multiple objectives: preferences and value tradeoffs , 1976 .

[6]  David Pisinger,et al.  Interactive Cost Configuration Over Decision Diagrams , 2014, J. Artif. Intell. Res..

[7]  Raimo P. Hämäläinen,et al.  Preference Programming - Multicriteria Weighting Models under Incomplete Information , 2010 .

[8]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[9]  Jeffrey M. Keisler,et al.  Portfolio decision analysis : improved methods for resource allocation , 2011 .

[10]  Shuzo Yajima,et al.  Size of Ordered Binary Decision Diagrams Representing Threshold Functions , 1996, Theor. Comput. Sci..

[11]  Matteo Fischetti,et al.  A new dominance procedure for combinatorial optimization problems , 1988 .

[12]  Murat Köksalan,et al.  Finding all nondominated points of multi-objective integer programs , 2013, J. Glob. Optim..

[13]  Anita Schöbel,et al.  Robustness for uncertain multi-objective optimization: a survey and analysis of different concepts , 2016, OR Spectr..

[14]  Ahti Salo,et al.  Preference programming for robust portfolio modeling and project selection , 2007, Eur. J. Oper. Res..

[15]  D. N. Kleinmuntz Advances in Decision Analysis: Resource Allocation Decisions , 2007 .

[16]  Xavier Gandibleux,et al.  A survey and annotated bibliography of multiobjective combinatorial optimization , 2000, OR Spectr..

[17]  Juuso Liesiö,et al.  Measurable Multiattribute Value Functions for Portfolio Decision Analysis , 2014, Decis. Anal..

[18]  Sofia Cassel,et al.  Graph-Based Algorithms for Boolean Function Manipulation , 2012 .

[19]  Ahti Salo,et al.  Robust portfolio modeling with incomplete cost information and project interdependencies , 2008, Eur. J. Oper. Res..

[20]  Ahti Salo,et al.  Expert judgments in the cost-effectiveness analysis of resource allocations: a case study in military planning , 2014, OR Spectr..

[21]  Kamal Golabi,et al.  Selecting a Portfolio of Solar Energy Projects Using Multiattribute Preference Theory , 1981 .

[22]  Markus Behle,et al.  Binary decision diagrams and integer programming , 2007 .

[23]  Randal E. Bryant,et al.  Efficient implementation of a BDD package , 1991, DAC '90.

[24]  Ahti Salo,et al.  A Resource Allocation Model for R&D Investments - A Case Study in Telecommunication Standardization , 2011 .