Adapting Ant Colony for Topology Optimization of Compliant Mechanisms With Variable Material Density

2017 ◽  
Author(s):  
Nadim Diab
Keyword(s):  
Topology Optimization ◽  
Ant Colony Optimization ◽  
High Performance ◽  
Compliant Mechanisms ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Ant Colony ◽  
Intensity Level ◽  
Material Density ◽  
Swarm Intelligence Optimization

Swarm intelligence optimization techniques are widely used in topology optimization of compliant mechanisms. The Ant Colony Optimization has been implemented in various forms to account for material density distribution inside a design domain. In this paper, the Ant Colony Optimization technique is applied in a unique manner to make it feasible to optimize for the beam elements’ cross-section and material density simultaneously. The optimum material distribution algorithm is governed by two various techniques. The first technique treats the material density as an independent design variable while the second technique correlates the material density with the pheromone intensity level. Both algorithms are tested for a micro displacement amplifier and the resulting optimized topologies are benchmarked against reported literature. The proposed techniques culminated in high performance and effective designs that surpass those presented in previous work.

scholarly journals Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques

2017 ◽  
Vol 12 (4) ◽  
pp. 12-25 ◽  
Author(s):  
Ibraheem Kasim Ibraheem ◽  
Fatin Hassan Ajeil
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Optimization ◽  
Multiple Testing ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Ant Colony ◽  
Testing Environments ◽  
Actual Size ◽  
Robot Path

This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of ACO algorithm for the same problem with the same environmental conditions by providing the shortest path for multiple testing environments.

scholarly journals COMPREHENSIVE REVIEW ON HEART DISEASE PREDICTION USING OPTIMIZATION TECHNIQUES

2020 ◽  
pp. 7-13
Author(s):  
Saranya S ◽  
Deepika P ◽  
Dr.Sasikala S
Keyword(s):  
Heart Disease ◽  
Ant Colony Optimization ◽  
Heart Attack ◽  
Data Extraction ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Ant Colony ◽  
Disease Prediction ◽  
Common Belief ◽  
The World

Heart disease is one of the main sources of demise around the world. It is imperative to predict the disease at a premature phase. The computer aided systems help the doctor as a tool for predicting and diagnosing heart attack. This research mainly focuses on the study of women heart attack prediction are analysed. Heart disease is the leading cause of death for both men and women. The early symptoms of heart attack can be quite different from men & women. It is a common belief that women are better at looking their health than men. But when it comes to heart health, research shows that many women don’t and often put the needs of others before themselves. In this study we studied various available techniques and diagnosis of heart attack disease with a sophisticated approach to data extraction, the Ant Colony Optimization technique. KEYWORDS: data mining, Heart disease, Ant colony optimization, pheromone

scholarly journals High-Level Parallel Ant Colony Optimization with Algorithmic Skeletons

2021 ◽  
Author(s):  
Breno A. de Melo Menezes ◽  
Nina Herrmann ◽  
Herbert Kuchen ◽  
Fernando Buarque de Lima Neto
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Optimization Problems ◽  
Programming Model ◽  
Parallel Implementation ◽  
Ant Colony ◽  
Algorithmic Skeletons ◽  
Low Level ◽  
Programming Patterns ◽  
High Level

AbstractParallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution time when solving complex optimization problems. When aiming for a GPU environment, developing efficient parallel versions of such algorithms using CUDA can be a difficult and error-prone task even for experienced programmers. To overcome this issue, the parallel programming model of Algorithmic Skeletons simplifies parallel programs by abstracting from low-level features. This is realized by defining common programming patterns (e.g. map, fold and zip) that later on will be converted to efficient parallel code. In this paper, we show how algorithmic skeletons formulated in the domain specific language Musket can cope with the development of a parallel implementation of ACO and how that compares to a low-level implementation. Our experimental results show that Musket suits the development of ACO. Besides making it easier for the programmer to deal with the parallelization aspects, Musket generates high performance code with similar execution times when compared to low-level implementations.

Sizing of current conveyors by means of an Ant Colony Optimization technique

2011 ◽  
Author(s):  
Bachir Benhala ◽  
Ali Ahaitouf ◽  
Abdellah Mechaqrane ◽  
Brahim Benlahbib ◽  
Farid Abdi ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Ant Colony ◽  
Current Conveyors

ACO powered by Local Searches Algorithms for the Solution of TSP Problems

2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Nisreen L. Ahmed
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Technique ◽  
General Purpose ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
New Approach ◽  
Local Searches ◽  
Probabilistic Technique ◽  
The Social ◽  
Great Deluge Algorithm

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and other animals. Ants, in particular, have inspired a number of methods and techniques among which the most studied and successful is the general-purpose optimization technique, also known as ant colony optimization, In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.  Ant Colony Optimization (ACO) algorithm is used to arrive at the best solution for TSP. In this article, the researcher has introduced ways to use a great deluge algorithm with the ACO algorithm to increase the ability of the ACO in finding the best tour (optimal tour). Results are given for different TSP problems by using ACO with great deluge and other local search algorithms.

Evolutionary Topology Optimization of Spatial Steel-Concrete Structures

2021 ◽  
Vol 62 (2) ◽  
pp. 102-112
Author(s):  
Yu Li ◽  
Yi Min Xie
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Principal Stresses ◽  
Element Analysis ◽  
Floor Systems ◽  
Beso Method ◽  
Multiple Materials ◽  
Single Material

Topology optimization techniques based on finite element analysis have been widely used in many fields, but most of the research and applications are based on single-material structures. Extended from the bi-directional evolutionary structural optimization (BESO) method, a new topology optimization technique for 3D structures made of multiple materials is presented in this paper. According to the sum of each element's principal stresses in the design domain, a material more suitable for this element would be assigned. Numerical examples of a steel- concrete cantilever, two different bridges and four floor systems are provided to demonstrate the effectiveness and practical value of the proposed method for the conceptual design of composite structures made of steel and concrete.

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