<p>In this work an investigation is performed in whether the algorithms Simultaneous Perturbation Stochastic Approximation (SPSA) and Virtual Force Algorithm (VFA) are suitable for real-time strategic placement of sensors in a dynamic environment. An evaluation of these algorithms is conducted and compared to Simulated Annealing (SA), which has been used before in similar applications.</p><p>For the tests, a computer based model of the sensors and the environment in which they are used, is implemented. The model handles sensors, moving objects, specifications for the area the sensors are supposed to monitor, and all interaction between components within the model.</p><p>It was the belief of the authors that SPSA and VFA are suited for this kind of problem, and that they have advantages over SA in complex scenarios. The results shows this to be true although SA seems to perform better when it comes to smaller number of sensors to be placed</p>

In this work an investigation is performed in whether the algorithms Simultaneous Perturbation Stochastic Approximation (SPSA) and Virtual Force Algorithm (VFA) are suitable for real-time strategic placement of sensors in a dynamic environment. An evaluation of these algorithms is conducted and compared to Simulated Annealing (SA), which has been used before in similar applications. For the tests, a computer based model of the sensors and the environment in which they are used, is implemented. The model handles sensors, moving objects, specifications for the area the sensors are supposed to monitor, and all interaction between components within the model. It was the belief of the authors that SPSA and VFA are suited for this kind of problem, and that they have advantages over SA in complex scenarios. The results shows this to be true although SA seems to perform better when it comes to smaller number of sensors to be placed

L’efficacité des méthodes d’optimisation modernes, associée à l’augmentation des ressources informatiques, a conduit à la possibilité d’utiliser ces algorithmes d’optimisation en temps réel agissant dans des rôles critiques. Cependant, cela ne peut se produire sans porter une certaine attention à la validité de ces algorithmes. Ce doctorat traite de la vérification formelle des algorithmes d'optimisation convexe lors qu'ils sont utilisés pour la guidance de systèmes dynamiques. En outre, nous démontrons comment les preuves théoriques des algorithmes d'optimisation en temps réel peuvent être utilisées pour décrire les propriétés fonctionnelles au niveau du code, les rendant ainsi accessibles à la communauté des méthodes formelles. / The efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. However, this cannot happen without addressing proper attention to the soundness of these algorithms. This PhD thesis discusses the formal verification of convex optimization algorithms with a particular emphasis on receding-horizon controllers. Additionally, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the code level, thereby making it accessible for the formal methods community.