Planning as Optimization: Online Learning of Situations and Optimal Configurations - SASO 2019 - Accompanying material
Authors/Creators
- 1. Oakland University
- 2. University of Würzburg
- 3. Technical University of Munich
- 4. Humboldt-Universität zu Berlin
Description
These files are accompanying material for our submission "" to SASO 19:
Many approaches apply optimization techniques in SASs, mostly within the planning procedure, to generate new system configurations or adaptation plans. We performed an analysis of these techniques based on approaches published during the last ten years in conferences and journals related to self-adaptive systems (SASs), namely ACM Transactions on Autonomous and Adaptive System (TAAS), the International Conference on Autonomic Computing and Communications (ICAC), the International Conferences on Self-Adaptive and Self-Organizing Systems (SASO), the International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), and the Symposium on the Foundations of Software Engineering (FSE). We identified the use of 29 different techniques in 51 publications. This list shows that a large set of techniques from different classes such as probabilistic, combinatorial, evolutionary, stochastic, mathematical, and meta-heuristic optimization are applied in SASs.
We provide two files:
- List of References (SASO - References - Planning_as_Optimization.pdf)
- Dataset (SASO - Dataset - Planning_as_Optimization.xlsx)