A Comparison of Several Heuristic Algorithms for Solving High Dimensional Optimization Problems

The number of heuristic optimization algorithms has exploded over the last decade with new methods being proposed constantly. A recent overview of existing heuristic methods has listed over 130 algorithms. The majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claiming to be superior to other methods in terms of performance. However, most of these algorithms have been tested on relatively low dimensional problems, i.e., problems involving less than 30 parameters. With the recent emergence of Big Data, the existing optimization methods need to be tested to find those (un)suitable to handle highly dimensional problems. This paper represents an initial step in such direction. Three traditional heuristic algorithms are systematically analyzed and tested in detail for problems involving up to 100 parameters. Genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE) are compared in terms of accuracy and runtime, using several high dimensional standard benchmark functions

Vehicle Modelling and Washout Filter Tuning for the Chalmers Vehicle Simulator

In this work three washout filters [1][3][4][5] originally developed for NASA airplane simulators are considered for the Chalmers Vehicle Simulator (CVS). The Classical and Optimal washout filters are implemented for real-time use, while the Adaptive washout filter is tested only by off-line simulation. The washout filter parameters are tuned by optimization algorithms. A Genetic Algorithm is used to find a starting point in the parameter space for the ensuing local optimization where a Riccati Algebraic Solver and the Steepest Descent Method are used. The optimization is performed on a computer simulation model of the CVS, taking standard driving manoeuvres as inputs. The obtained Classical and Optimal washout filters were tested in real time on the CVS with several “test drivers”. During all the tests, the platform never hit the physical boundaries, but moved very close to them, thus using most of the actuator’s movement. According to the test drivers’ impressions, the washout filters produced realistic driving experience