An infinite-horizon multistage dynamic optimization problem

1995 ◽  
Vol 86 (3) ◽  
pp. 529-552 ◽  
Author(s):  
H. R. Babad
Keyword(s):  
Dynamic Optimization ◽  
Optimization Problem ◽  
Infinite Horizon ◽  
Dynamic Optimization Problem

scholarly journals Tracking Moving Optima Using Kalman-Based Predictions

2008 ◽  
Vol 16 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Claudio Rossi ◽  
Mohamed Abderrahim ◽  
Julio César Díaz
Keyword(s):  
Evolutionary Algorithms ◽  
Dynamic Optimization ◽  
Optimization Problem ◽  
Moving Objects ◽  
Fitness Landscape ◽  
Experimental Comparison ◽  
Motion Information ◽  
Dynamic Optimization Problem ◽  
First Order ◽  
Robotic Application

The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison.

scholarly journals Swarm algorithms in dynamic optimization problem of reactive power compensation units control

2019 ◽  
Vol 9 (5) ◽  
pp. 3967
Author(s):  
V.Z Manusov ◽  
P.V. Matrenin ◽  
N. Khasanzoda
Keyword(s):  
Dynamic Optimization ◽  
Power Supply ◽  
Optimization Problem ◽  
Power Supply System ◽  
Reactive Power ◽  
Reactive Power Compensation ◽  
Supply System ◽  
Bees Algorithm ◽  
Dynamic Optimization Problem ◽  
Engineering Research

Optimization of a power supply system is one of the main directions in power engineering research. The reactive power compensation reduces active power losses in transmission lines. In general, researches devoted to allocation and control of the compensation units consider this issue as a static optimization problem. However, it is dynamic and stochastic optimization problem that requires a real-time solution. To solve the dynamic optimization NP-hard problem, it is advisable to use Swarm Intelligence. This research deals with the problem of the compensation units power control as a dynamic optimization problem, considering the possible stochastic failures of the compensation units. The Particle Swarm Optimization and the Bees Algorithm were applied to solve it to compare the effectiveness of these algorithms in the dynamic optimization of a power supply system.

Sign in / Sign up

Export Citation Format

Share Document