scholarly journals Influence of the optimization methods on neural state estimation quality of the drive system with elasticity

2013 ◽  
Vol 24 (6) ◽  
pp. 1327-1340 ◽  
Author(s):  
Teresa Orlowska-Kowalska ◽  
Marcin Kaminski
Keyword(s):  
State Estimation ◽  
Optimization Methods ◽  
Drive System ◽  
Estimation Quality

Software suite for determining the tilts of tower-type structures according to terrestrial laser scanning

2020 ◽  
Vol 961 (7) ◽  
pp. 2-7
Author(s):  
A.V. Zubov ◽  
N.N. Eliseeva
Keyword(s):  
Laser Scanning ◽  
Optimization Problems ◽  
Optimization Methods ◽  
User Participation ◽  
Software Suite ◽  
Current State ◽  
Visual Basic For Applications ◽  
Operational Data ◽  
Theoretical Developments

The authors describe a software suite for determining tilt degrees of tower-type structures according to ground laser scanning indication. Defining the tilt of the pipe is carried out with a set of measured data through approximating the sections by circumferences. They are constructed using one of the simplest search engine optimization methods (evolutionary algorithm). Automatic filtering the scan of the current section from distorting data is performed by the method of assessing the quality of models constructed with that of least squares. The software was designed using Visual Basic for Applications. It contains several blocks (subprograms), with each of them performing a specific task. The developed complex enables obtaining operational data on the current state of the object with minimal user participation in the calculation process. The software suite is the result of practical implementing theoretical developments on the possibilities of using search methods at solving optimization problems in geodetic practice.

scholarly journals Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880113
Author(s):  
Miguel Angel Funes Lora ◽  
Edgar Alfredo Portilla-Flores ◽  
Raul Rivera Blas ◽  
Emmanuel Alejandro Merchán Cruz ◽  
Manuel Faraón Carbajal Romero
Keyword(s):  
Numerical Technique ◽  
Cuckoo Search ◽  
Optimization Methods ◽  
Metaheuristic Algorithms ◽  
End Effector ◽  
Bee Colony ◽  
Ill Posed ◽  
Metaheuristic Techniques

Many robots are dedicated to replicate trajectories recorded manually; the recorded trajectories may contain singularities, which occur when positions and/or orientations are not achievable by the robot. The optimization of those trajectories is a complex issue and classical optimization methods present a deficient performance when solving them. Metaheuristics are well-known methodologies for solving hard engineering problems. In this case, they are applied to obtain alternative trajectories that pass as closely as possible to the original one, reorienting the end-effector and displacing its position to avoid the singularities caused by limitations of inverse kinematics equations, the task, and the workspace. In this article, alternative solutions for an ill-posed problem concerning the behavior of the robotic end-effector position and orientation are proposed using metaheuristic algorithms such as cuckoo search, differential evolution, and modified artificial bee colony. The case study for this work considers a three-revolute robot (3R), whose trajectories can contain or not singularities, and an optimization problem is defined to minimize the objective function that represents the error of the alternative trajectories. A tournament in combination with a constant of proportionality allows the metaheuristics to modify the gradual orientation and position of the robot when a singularity is present. Consequently, the procedure selects from all the possible elbow-configurations the best that fits the trajectory. A classical numerical technique, Newton’s method, is used to compare the results of the applied metaheuristics, to evaluate their quality. The results of this implementation indicate that metaheuristic algorithms are an efficient tool to solve the problem of optimizing the end-effector behavior, because of the quality of the alternative trajectory produced.

scholarly journals Assessing ENSO Simulations and Predictions Using Adjoint Ocean State Estimation

2004 ◽  
Vol 17 (22) ◽  
pp. 4301-4315 ◽  
Author(s):  
Dietmar Dommenget ◽  
Detlef Stammer
Keyword(s):  
State Estimation ◽  
Positive Impact ◽  
Coupled Model ◽  
Estimation Procedure ◽  
Time Interval ◽  
Seasonal Forecasts ◽  
Predictive Skill ◽  
Sst Anomaly ◽  
Ocean State Estimation

Abstract Simulations and seasonal forecasts of tropical Pacific SST and subsurface fields that are based on the global Consortium for Estimating the Circulation and Climate of the Ocean (ECCO) ocean-state estimation procedure are investigated. As compared to similar results from a traditional ENSO simulation and forecast procedure, the hindcast of the constrained ocean state is significantly closer to observed surface and subsurface conditions. The skill of the 12-month lead SST forecast in the equatorial Pacific is comparable in both approaches. The optimization appears to have better skill in the SST anomaly correlations, suggesting that the initial ocean conditions and forcing corrections calculated by the ocean-state estimation do have a positive impact on the predictive skill. However, the optimized forecast skill is currently limited by the low quality of the statistical atmosphere. Progress is expected from optimizing a coupled model over a longer time interval with the coupling statistics being part of the control vector.

scholarly journals Comparison of Multicast Algorithm Evaluation Results in Low and High Multicast Saturation Environments

2019 ◽  
Vol 3 ◽  
pp. 3-7
Author(s):  
Krzysztof Stachowiak ◽  
Piotr Zwierzykowski
Keyword(s):  
Quality Of Service ◽  
Computational Complexity ◽  
Optimization Methods ◽  
The Other ◽  
Ongoing Research ◽  
Mathematical Problems ◽  
Point To Point ◽  
Difficult Challenge ◽  
Entire Network

The multicast quality of service-enabled routing is a computationally challenging task. Despite ongoing research efforts, the associated mathematical problems are still considered to be NP-hard. In certain applications, computational complexity of finding the optimal connection between a set of network devices may be a particularly difficult challenge. For example, connecting a small group of participants of a teleconference is not much more complex than setting up a set of mutual point-to-point connections. On the other hand, satisfying the demand for such services as IPTV, with their receivers constituting the majority of the network, requires applying appropriate optimization methods in order to ensure real system execution. In this paper, algorithms solving this class of problems are considered. The notion of multicast saturation is introduced to measure the amount of multicast participants relative to the entire network, and the efficiency of the analyzed algorithms is evaluated for different saturation degrees.

Optimized Crossover JumpX in Genetic Algorithm for General Routing Problems

2018 ◽  
pp. 205-230
Author(s):  
Hicham El Hassani ◽  
Said Benkachcha ◽  
Jamal Benhra
Keyword(s):  
Genetic Algorithm ◽  
Optimization Methods ◽  
Search Space ◽  
Optimal Solutions ◽  
Solution Quality ◽  
Path Representation ◽  
Representation Technique ◽  
Hard Problems ◽  
The Traveling Salesman Problem

Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is one of the most studied Supply chain management problems. This paper proposes a new crossover operator called Jump Crossover (JMPX) for solving the travelling salesmen problem using a genetic algorithm (GA) for near-optimal solutions, to conclude on its efficiency compared to solutions quality given by other conventional operators to the same problem, namely, Partially matched crossover (PMX), Edge recombination Crossover (ERX) and r-opt heuristic with consideration of computational overload. We adopt the path representation technique for our chromosome which is the most direct representation and a low mutation rate to isolate the search space exploration ability of each crossover. The experimental results show that in most cases JMPX can remarkably improve the solution quality of the GA compared to the two existing classic crossover approaches and the r-opt heuristic.

scholarly journals Technical Solution of the Drive System for Mixing Dough Machine

2019 ◽  
Vol 290 ◽  
pp. 08013
Author(s):  
Aleksandar Miltenović ◽  
Milan Banić ◽  
Nikola Velimirović
Keyword(s):  
Global Economy ◽  
Food Products ◽  
Drive System ◽  
Design Solution ◽  
Medium Size ◽  
Technical Solution ◽  
Complete Space ◽  
Quality Of Food ◽  
Noise And Vibration Reduction

In the conditions of the global economy, food industry products have a good share in international trade. It is primarily ready-made food products that are ready for use. The basic problem that needs to be solved is the safety and quality of food products. Machine “Planetary mixer” is used for mixing and preparing dough. From the aspect of optimal fulfilment of the working function of the preparing dough “Planetary mixer” has to fulfil the following conditions: - the complete space in which the dough is located must be treated equally with the mixer; - noise and vibration reduction should be ensured and appropriate precision positioning of the machinery’s executive bodies; - a compact construction of the drive system is required with the optimum utilization of the available resources. In the paper is presented technical design solution of the drive system for machine based on the demands of regional medium size enterprise and therefore it is limited to the requirements of the investor. The final solution was achieved by using the modern methods of product development.

SIMULATION OPTIMIZATION: APPLICATIONS IN RISK MANAGEMENT

2008 ◽  
Vol 07 (04) ◽  
pp. 571-587 ◽  
Author(s):  
MARCO BETTER ◽  
FRED GLOVER ◽  
GARY KOCHENBERGER ◽  
HAIBO WANG
Keyword(s):  
Risk Management ◽  
Business Process ◽  
Process Design ◽  
Simulation Optimization ◽  
Optimization Methods ◽  
Optimization Approach ◽  
Risk And Uncertainty ◽  
Business Process Design ◽  
Managing Risk

Simulation optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of simulation optimization for managing risk. Recent advances in simulation optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk and uncertainty, simulation optimization surpasses the capabilities of other optimization methods not only in the quality of solutions but also in their interpretability and practicality. In this paper, we demonstrate the advantages of using a simulation optimization approach to tackle risky decisions, by showcasing the methodology on two popular applications from the areas of finance and business process design.

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