Focusing on Important Problems



Published Jan 18, 2023
Hannele Wallenius Jyrki Wallenius


Research in Multiple Criteria Decision Making (MCDM) and its subfields (multi-attribute utility theory or Decision Analysis, AHP, Goal Programming, MCDA, multi-objective mathematical programming, EMO) is very active. However, our general feeling is that bright, young people do not focus their energies sufficiently on solving important problems despite many very important problems that deserve attention. Some of the problems are critical to the well-being of the world. The purpose of our essay is to identify these very important problems (or mega trends, as they are sometimes called) and briefly discuss how the research community could help solve or at least alleviate such problems. The reader could interpret our essay as suggestions for a research agenda or program. It does not matter whether we are AHP scholars, multi-objective optimizers, or decision analysts, everyone’s contribution is needed.

How to Cite

Wallenius , H., & Wallenius, J. (2023). Focusing on Important Problems. International Journal of the Analytic Hierarchy Process, 14(3).


Download data is not yet available.
Abstract 39 | PDF Downloads 34



Internet of Things, mega trends, Big Data, Artificial Intelligence, Conflict resolution and disarmament

Brechbuhl, H. World Economic Forum. (2015).

eCommerce Relevance Report by COVEO. (2022).

Hallerbach, W., Ning, H., Soppe, A., and Spronk, J. (2004). A framework for managing a portfolio of socially responsible investments. European Journal of Operational Research, 153(2), 517-529. Doi:

Hobbs, B. and P. Meier (2003). Energy decisions and the environment: A guide to the use of multi-criteria methods. Boston: Kluwer Academic.

Keeney, R. and H. Raiffa (1976). Decisions with multiple objectives: Preferences and value tradeoffs. New York: Wiley.

Markowitz, H. (1952). Portfolio selection, Journal of Finance, 7(1), 77-91. Doi:

Pham, L., Teich, J., Wallenius, H., and Wallenius, J. (2015). Multi-attribute online reverse auctions: Recent research trends. European Journal of Operational Research, 242(1), 1-9. Doi:
Roy, A., Mackin, P., Wallenius, J., Corner, J., Keith, M., Schymik, G., and H. Arora (2008). An interactive search method based on user preferences. Decision Analysis, 5(4), 203-22. Doi:

Saaty, T. L. (1968). Mathematical models of arms control and disarmament: Application of mathematical structures in politics. John Wiley & Sons.

Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, priority setting, resource allocation. New York: McGraw-Hill.

Saaty, T.L., Zoffer, H. J., Vargas, L.G., and Guiora, A. (2022). Overcoming the retributive nature of the Israeli-Palestinian conflict. Switzerland: Springer Nature. Doi:

Schildt, H. (2020). The data imperative: How digitalization is reshaping management, organizing and work. Oxford: Oxford University Press. Doi:

Teich, J., Wallenius, H., Wallenius, J. and A. Zaitsev (2001). Designing electronic auctions: An Internet-based hybrid procedure combining aspects of negotiations and auctions. Electronic Commerce Research, 1, 301-314. Doi:

Wallenius, H. and Wallenius, J. (2022). How can decision sciences and MCDM help solve challenging world problems. In S. Greco, V. Mousseau, J. Stefanowski, and C. Zopounidis (Eds), Intelligent decision support systems (pp 59-71). Springer. Doi:
Essays, Reviews & Comments