Contributed Session Wed.2.H 3503

Wednesday, 13:15 - 14:45 h, Room: H 3503

Cluster 6: Derivative-free & simulation-based optimization [...]

Derivative-free applications and parallelization


Chair: Luís Nunes Vicente and Stefan Wild



Wednesday, 13:15 - 13:40 h, Room: H 3503, Talk 1

Aurea Martinez
Design of river fishways: A derivative-free optimization perspective

Coauthors: Lino J. Alvarez-Vazquez, Carmen Rodriguez, Miguel E. Vazquez-Mendez, Miguel A. Vilar


The main objective of this talk consists of presenting an application of mathematical simulation and optimal control theory to an ecological engineering problem related to preserve and enhance natural stocks of fish which migrate between salt and fresh water. River fishways are hydraulic structures that enable fish to overcome stream obstructions (as dams in hydroelectric power plants). Particularly, we are interested in improving the optimal shape design of these fishways. The problem can be formulated within the framework of the optimal control of partial differential equations, approximated by a discrete optimization problem, and solved by using a gradient-free method (the Nelder-Mead algorithm). Finally, numerical results are shown for a standard real-world situation, and compared to the results recently achieved by the authors in a joint work with J. Judice via a gradient-type method (a spectral projected gradient algorithm).



Wednesday, 13:45 - 14:10 h, Room: H 3503, Talk 2

A. Ismael F. Vaz
Vibration-based structural health monitoring based on a derivative-free global optimization approach

Coauthors: Paulo J. Antunes, Rui J. Guimarães, Júlio C. Viana


Structural health monitoring (SHM) of critical parts is assuming a relevant role in several engineering fields such as civil, aeronautical and aerospatial. Several SHM techniques are able to determine the presence of structural damage. However, the location and damage severity estimation are more difficult to determine.
In this talk, a new SHM approach based on optimization techniques is shown. This method is capable of, simultaneously, locate, determine the type of damage and output its severity. The considered objective function measures how well structural damage simulated data (obtained by using finite element models) compares with the observed data from the (un)damaged part in service. For 2D parts, four damage spatial variables and three material properties variables are considered. Due to the simulation process involved, objective function derivatives are unavailable and the objective function evaluations are costly. Numerical results also show that, in order to properly determine the damage location and severity, the optimization problem has to be solved globally. We present some successful numerical results using the PSwarm solver.



Wednesday, 14:15 - 14:40 h, Room: H 3503, Talk 3

Per-Magnus Olsson
Parallelization of algorithms for derivate-free optimization

Coauthors: Holmberg Kaj, Olsson Per-Magnus


In this talk we present parallelization and extensions of algorithms for derivative-free optimization. In each iteration, we run several instances of an optimization algorithm with different trust region parameters, and each instance generates a point for evaluation. All points are kept in a common priority queue and the most promising points are evaluated in parallel when computers are available. We use models from several instances to prioritize the points and in case new information becomes available, we allow dynamic prioritization of points to ensure that computational resources are used efficiently. A database is used to avoid reevaluation of points. Together, these extensions make it easier to find several local optima and rank them against each other, which is very useful when performing robust optimization. Empirical testing reveals considerable decreases in the number of function evaluations as well as in the time required to solve problems.


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