Document Type

Article

Publication Date

2022

DOI

10.3390/info13100469

Publication Title

Information

Volume

13

Issue

10

Pages

469 (15 pp.)

Abstract

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about the system and the outcomes of interest. Complex adaptive systems under deep uncertainty must integrate the search for robust solutions by conducting exploratory modeling and analysis. This article visits both domains, shows what the new challenges are, and provides a framework to apply methods from operational research and complexity science to address them. With such extensions, simulation-based approaches will be able to support these new areas as well, although optimal solutions may no longer be obtainable. Instead, robust and sufficient solutions will become the objective of optimization processes.

Rights

Copyright: © 2022 by the The MITRE Corporation. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).

Data Availability

Article states not applicable.

Original Publication Citation

Tolk, A. (2022). Simulation-based optimization: Implications of complex adaptive systems and deep uncertainty. Information, 13(10), Article 469. https://doi.org/10.3390/info13100469

ORCID

0000-0002-4201-8757 (Tolk)

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