scholarly journals Path Planning for an HEXA Parallel Mechanism using a Modified PSO Algorithm

2021 ◽  
Author(s):  
Lucian Milica ◽  
Adina Milica
Keyword(s):  
Parallel Mechanism ◽  
Characteristic Point ◽  
Hermite Polynomials ◽  
Mathematical Formulation ◽  
Pso Algorithm ◽  
Search Space ◽  
Computational Effort ◽  
Hermite Functions ◽  
End Effector ◽  
Modified Pso

Abstract This paper presents a method for determining the optimal trajectory of the characteristic point based on the kinematic analysis of a HEXA parallel mechanism. The optimization was performed based on a modified PSO algorithm based on Hermite polynomials (MH-PSO). The change made to the initial algorithm consists in restricting the search space of the solutions by using the Hermite polynomial expressions of the geometric parameters as time functions for defining the movements of the end-effector. The MH-PSO algorithm, from its inception, ensures a faster convergence of solutions and ease of computational effort and is the main advantage of the method presented. During the optimization process, the function followed was the length of the trajectory described by the sequence of positions of the characteristic point, belonging to the end effector element, in compliance with additional conditions imposed. The use of the Hermite functions and PSO algorithm leads to minimal effort for analysis and mathematical formulation of the optimization problem.

Train Planning on a Single Track Shared-Use Passenger and Freight Corridor With Demand Considerations

2014 ◽  
Author(s):  
Ahmadreza Talebian ◽  
Bo Zou
Keyword(s):  
Marginal Cost ◽  
Mathematical Formulation ◽  
Computation Time ◽  
Search Space ◽  
Computational Effort ◽  
Scheduling Problem ◽  
Sequential Approach ◽  
Train Scheduling ◽  
Passenger Train ◽  
Passenger Trains

While the train scheduling problem has been investigated for an extended period of time, shared passenger and freight corridor planning and capacity analysis have gained growing attention recently, due largely to the emergence of higher speed rail lines in the US. This study proposes an integrated, hypergraph-based approach that considers constraints from infrastructure supply as well as passenger demand in solving the train scheduling problem on a passenger-freight shared rail corridor. Two approaches are proposed to capture different policies which could be implemented in real world. The first, sequential approach considers passenger train priority in schedule planning, and then develop freight trains schedules given the fixed schedule of passenger trains. In the second approach, we minimize the total costs of freight and passenger trains simultaneously. Our results indicates that the marginal cost increase for freight railroad due to considering passenger train priority is larger than the associated marginal cost reduction for passengers. We also find that using high resolution time units in the mathematical formulation does not significantly improve the solution, meanwhile causing substantial increase in computation time. Therefore we suggest choosing coarser a time unit to first generate an approximate solution, which is subsequently used to reduce the search space for feasible train schedules using a finer-grained time unit. We show that this considerably saves computational effort.

Operation sequencing optimization for five-axis prismatic parts using a particle swarm optimization approach

2009 ◽  
Vol 223 (5) ◽  
pp. 485-497 ◽  
Author(s):  
Y W Guo ◽  
A R Mileham ◽  
G W Owen ◽  
P G Maropoulos ◽  
W D Li
Keyword(s):  
Particle Swarm Optimization ◽  
Process Planning ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Operation Sequencing ◽  
Swarm Optimization ◽  
Process Plan ◽  
Five Axis ◽  
Modified Pso

Operation sequencing is one of the crucial tasks in process planning. However, it is an intractable process to identify an optimized operation sequence with minimal machining cost in a vast search space constrained by manufacturing conditions. Also, the information represented by current process plan models for three-axis machining is not sufficient for five-axis machining owing to the two extra degrees of freedom and the difficulty of set-up planning. In this paper, a representation of process plans for five-axis machining is proposed, and the complicated operation sequencing process is modelled as a combinatorial optimization problem. A modern evolutionary algorithm, i.e. the particle swarm optimization (PSO) algorithm, has been employed and modified to solve it effectively. Initial process plan solutions are formed and encoded into particles of the PSO algorithm. The particles ‘fly’ intelligently in the search space to achieve the best sequence according to the optimization strategies of the PSO algorithm. Meanwhile, to explore the search space comprehensively and to avoid being trapped into local optima, several new operators have been developed to improve the particle movements to form a modified PSO algorithm. A case study used to verify the performance of the modified PSO algorithm shows that the developed PSO can generate satisfactory results in optimizing the process planning problem.

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

Kinematic analysis and design of a novel 6-degree of freedom parallel robot

2014 ◽  
Vol 229 (2) ◽  
pp. 291-303 ◽  
Author(s):  
DU Hui ◽  
GAO Feng ◽  
PAN Yang
Keyword(s):  
Set Theory ◽  
Kinematic Analysis ◽  
Parallel Mechanism ◽  
Design Methodology ◽  
Parallel Robot ◽  
End Effector ◽  
Analysis And Design ◽  
Velocity Models ◽  
Reachable Workspace ◽  
Rotational Motions

A novel 3-UP3R parallel mechanism with six degree of freedoms is proposed in this paper. One most important advantage of this mechanism is that the three translational and three rotational motions are partially decoupled: the end-effector position is only determined by three inputs, while the rotational angles are relative to all six inputs. The design methodology via GF set theory is brought out, using which the limb type can be determined. The mobility of the end-effector is analyzed. After that, the kinematic and velocity models are formulated. Then, workspace is studied, and since the robot is partially decoupled, the reachable workspace is also the dexterous workspace. In the end, both local and global performances are discussed using conditioning indexes. The experiment of real prototype shows that this mechanism works well and may be applied in many fields.

Improved Particle Swarm Optimizer with Dynamically Adjusted Search Space and Velocity Limits for Global Optimization

2015 ◽  
Vol 24 (05) ◽  
pp. 1550017 ◽  
Author(s):  
Aderemi Oluyinka Adewumi ◽  
Akugbe Martins Arasomwan
Keyword(s):  
Global Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Particle Swarm Optimizer ◽  
Search Range ◽  
Original Algorithm ◽  
Inertia Weight ◽  
And Performance

This paper presents an improved particle swarm optimization (PSO) technique for global optimization. Many variants of the technique have been proposed in literature. However, two major things characterize many of these variants namely, static search space and velocity limits, which bound their flexibilities in obtaining optimal solutions for many optimization problems. Furthermore, the problem of premature convergence persists in many variants despite the introduction of additional parameters such as inertia weight and extra computation ability. This paper proposes an improved PSO algorithm without inertia weight. The proposed algorithm dynamically adjusts the search space and velocity limits for the swarm in each iteration by picking the highest and lowest values among all the dimensions of the particles, calculates their absolute values and then uses the higher of the two values to define a new search range and velocity limits for next iteration. The efficiency and performance of the proposed algorithm was shown using popular benchmark global optimization problems with low and high dimensions. Results obtained demonstrate better convergence speed and precision, stability, robustness with better global search ability when compared with six recent variants of the original algorithm.

Experimental Validation of the Kinematics of a 3PRS Compliant Mechanism for Micromilling

2015 ◽  
Author(s):  
Antonio Ruiz ◽  
Francisco Campa Gomez ◽  
Constantino Roldan-Paraponiaris ◽  
Oscar Altuzarra
Keyword(s):  
Parallel Mechanism ◽  
Degrees Of Freedom ◽  
Experimental Validation ◽  
Compliant Mechanism ◽  
Motion Controller ◽  
End Effector ◽  
Compliant Joints ◽  
Hybrid Manipulator ◽  
Compliant Parallel Mechanism ◽  
Actuated Joints

The present work deals with the development of a hybrid manipulator of 5 degrees of freedom for milling moulds for microlenses. The manipulator is based on a XY stage under a 3PRS compliant parallel mechanism. The mechanism takes advantage of the compliant joints to achieve higher repetitiveness, smoother motion and a higher bandwidth, due to the high precision demanded from the process, under 0.1 micrometers. This work is focused on the kinematics of the compliant stage of the hybrid manipulator. First, an analysis of the workspace required for the milling of a single mould has been performed, calculating the displacements required in X, Y, Z axis as well as two relative rotations between the tool and the workpiece from a programmed toolpath. Then, the 3PRS compliant parallel mechanism has been designed using FEM with the objective of being stiff enough to support the cutting forces from the micromilling, but flexible enough in the revolution and spherical compliant joints to provide the displacements needed. Finally, a prototype of the 3PRS compliant mechanism has been built, implementing a motion controller to perform translations in Z direction and two rotations. The resulting displacements in the end effector and the actuated joints have been measured and compared with the FEM calculations and with the rigid body kinematics of the 3PRS.

scholarly journals Optimized Traffic Grooming through modified PSO based Iterative Hungarian algorithm in Optical Networks

2021 ◽  
Vol 50 (3) ◽  
pp. 546-557
Author(s):  
J. KUMARNATH ◽  
K. BATRI
Keyword(s):  
Performance Analysis ◽  
Optical Networks ◽  
Performance Measures ◽  
Shortest Path ◽  
Optical Network ◽  
Traffic Grooming ◽  
Pso Algorithm ◽  
Propagation Delay ◽  
The Other ◽  
Modified Pso

Due to huge size of the data and quick transmission of data between the nodes present in the optical network, a condition of network traffic is created among the nodes of the network. This issue of traffic can be overcome by employing numerous traffic grooming techniques. In this research paper, the best suitable shortest path is determined by the multi objective modified PSO algorithm and an innovative visibility graph based Iterative Hungarian Traffic grooming algorithm is implemented to reduce the blocking ratio through improving the allocation of bandwidth between the users. Then finally the performance analysis is carried out by means of performance measures such as traffic throughput, transceivers count, average propagation delay, blocking ratio, and success ratio. It can be inferred that the proposed work obtains enhanced outcomes when compared to the other existing techniques.

scholarly journals Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space

2014 ◽  
Author(s):  
Richard Wilton ◽  
Tamas Budavari ◽  
Ben Langmead ◽  
Sarah J Wheelan ◽  
Steven Salzberg ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
High Throughput ◽  
Search Space ◽  
Computational Effort ◽  
Biological Sequences ◽  
Reduction Techniques ◽  
Software Implementations ◽  
List Processing ◽  
High Processing

Motivation: In computing pairwise alignments of biological sequences, software implementations employ a variety of heuristics that decrease the computational effort involved in computing potential alignments. A key element in achieving high processing throughput is to identify and prioritize potential alignments where high-scoring mappings can be expected. These tasks involve list-processing operations that can be efficiently performed on GPU hardware. Results: We implemented a read aligner called A21 that exploits GPU-based parallel sort and reduction techniques to restrict the number of locations where potential alignments may be found. When compared with other high-throughput aligners, this approach finds more high-scoring mappings without sacrificing speed or accuracy. A21 running on a single GPU is about 10 times faster than comparable CPU-based tools; it is also faster and more sensitive in comparison with other recent GPU-based aligners.

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