scholarly journals Application of the Bees Algorithm for Constrained Mechanical Design Optimisation Problem

2019 ◽  
Vol 4 (1) ◽  
pp. 27-32
Author(s):  
Shafie Kamaruddin ◽  
Mohd Arif Hafizi Abd Latif
Keyword(s):  
Honey Bees ◽  
Foraging Behaviour ◽  
Feasible Solution ◽  
Mechanical Design ◽  
Optimal Solution ◽  
Ant Colony ◽  
Bees Algorithm ◽  
Ant Colony Optimisation ◽  
Teaching Learning ◽  
Optimisation Algorithms

Optimisation is a technique or procedure to find the optimal or feasible solution whether it is to minimise or maximise by comparing other possible solutions until the best solution is found. Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. The Bees Algorithm is considered as one of the best optimisation algorithms because it has been successfully solved different type optimisation problem from in various field. It is inspired by the foraging behaviour of honey bees in nature. This study applies the Bees Algorithm to minimise the mass of disc clutch brake in its design. To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.

scholarly journals Ant Colony Optimisation for Backward Production Scheduling

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Leandro Pereira dos Santos ◽  
Guilherme Ernani Vieira ◽  
Higor Vinicius dos R. Leite ◽  
Maria Teresinha Arns Steiner
Keyword(s):  
Production Scheduling ◽  
Food Industry ◽  
Optimal Solution ◽  
Computer Time ◽  
Ant Colony ◽  
Shop Floor ◽  
Ant Colony Optimisation ◽  
Complex Environment ◽  
Artificial Intelligence Technique ◽  
Scheduling System

The main objective of a production scheduling system is to assign tasks (orders or jobs) to resources and sequence them as efficiently and economically (optimised) as possible. Achieving this goal is a difficult task in complex environment where capacity is usually limited. In these scenarios, finding an optimal solution—if possible—demands a large amount of computer time. For this reason, in many cases, a good solution that is quickly found is preferred. In such situations, the use of metaheuristics is an appropriate strategy. In these last two decades, some out-of-the-shelf systems have been developed using such techniques. This paper presents and analyses the development of a shop-floor scheduling system that uses ant colony optimisation (ACO) in a backward scheduling problem in a manufacturing scenario with single-stage processing, parallel resources, and flexible routings. This scenario was found in a large food industry where the corresponding author worked as consultant for more than a year. This work demonstrates the applicability of this artificial intelligence technique. In fact, ACO proved to be as efficient as branch-and-bound, however, executing much faster.

scholarly journals Application of two ant colony optimisation algorithms to water distribution system optimisation

2006 ◽  
Vol 44 (5-6) ◽  
pp. 451-468 ◽  
Author(s):  
Aaron C. Zecchin ◽  
Angus R. Simpson ◽  
Holger R. Maier ◽  
Michael Leonard ◽  
Andrew J. Roberts ◽  
...  
Keyword(s):  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
System Optimisation ◽  
Optimisation Algorithms

scholarly journals Τεχνικές οδήγησης και εντοπισμού πληροφορίας στον κυβερνοχώρο, βασισμένες σε μοντέλα φυσικών διαδικασιών

2007 ◽  
Author(s):  
Γεώργιος Κούζας
Keyword(s):  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Optimisation Algorithms

Η Διατριβή αυτή διαπραγματεύεται μια τροποποίηση του αλγόριθμου Ant-Miner που ανήκει στην οικογένεια των αλγορίθμων ACO (Ant-Colony Optimisation algorithms).

Optimal design of mechanical components using the Bees Algorithm

2008 ◽  
Vol 223 (5) ◽  
pp. 1051-1056 ◽  
Author(s):  
D T Pham ◽  
A Ghanbarzadeh ◽  
S Otri ◽  
E Koç
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Honey Bees ◽  
Mechanical Design ◽  
Optimization Techniques ◽  
Bees Algorithm ◽  
Search Procedure ◽  
Robust Performance ◽  
Beam Structure ◽  
Design Problems

This paper describes the first application of the Bees Algorithm to mechanical design optimization. The Bees Algorithm is a search procedure inspired by the way honey bees forage for food. Two standard mechanical design problems, the design of a welded beam structure and the design of coil springs, were used to benchmark the Bees Algorithm against other optimization techniques. The paper presents the results obtained showing the robust performance of the Bees Algorithm.

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