Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In this work, the problem of node distribution is formulated as an optimization problem, which is to be included in the underlying non-linear mathematical programming problem (NLP). The benefits of utilizing the suggested method for on-line trajectory optimization are ...

Neural networks and the Kriging method are compared for constructing fitness approximation models in evolutionary optimization algorithms. The two models are applied in an identical framework to the optimization of a number of well known test functions. In addition, two different ways of training the approximators are evaluated: In one setting the models are built off-line using data from previ...

In order to track and estimate the pose of known rigid objects with high accuracy in unconstrained environment with light disturbance, scale changes and occlusion, we propose to combine 3D particle filter (PF) framework with algebraic pose optimization in a closed loop. A new PF observation model based on line similarity in 3D space is devised and the output of 3D PF tracking, namely line corre...

Manufacturing is a challenging real-world domain for studying hierarchical MDP-based optimization algorithms. We have recently obtained very promising results using a hierarchical reinforcement learning based optimization algorithm for a 12-machine transfer line. Transfer lines model factory processes in automobile and many other product assembly plants. Unlike domains such as elevator scheduli...

Optimal capacitor placement, considering power system loss reduction, voltage profile improvement, line reactive power decrease and power factor correction, is of particular importance in power system planning and control. The distribution system operator calculates the optimal place, number and capacity of capacitors based on two major purposes: active power loss reduction and return on invest...

‎Newton method is one of the most famous numerical methods among the line search‎ ‎methods to minimize functions. ‎It is well known that the search direction and step length play important roles ‎in this class of methods to solve optimization problems. ‎In this investigation‎, ‎a new modification of the Newton method to solve ‎unconstrained optimization problems is presented‎. ‎The significant ...

Congestion management is one of the major tasks performed by system operators (SOs) to ensure the operation of transmission system within operating limits. To permit smooth and quality flow of power the problem of congestion has to be solved. The congestion in the transmission line will be removed by generation rescheduling with the cost involved in the rescheduling process should be minimized....

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.02.014 * Corresponding author. E-mail addresses: [email protected] (R. Roy), (S.P. Ghoshal). In this paper, various novel heuristic stochastic search techniques have been proposed for optimization of proportional–integral-derivative gains used in Sugeno fuzzy logic based automatic generation control of multi-area ther...

This report presents P scg , a new global optimization method for training mul-tilayered perceptrons. Instead of local minima, global minima of the error function are found. This new method is hybrid in the sense that it combines three very diierent optimization techniques: Random Line Search, Scaled Conjugate Gradient and a 1-dimensional minimization algorithm named P. The best points of each ...