رکورد قبلیرکورد بعدی

" Improved versions of the bees algorithm for global optimisation "


Document Type : Latin Dissertation
Record Number : 807243
Doc. No : TLets742620
Main Entry : Kamaruddin, Shafie
Title & Author : Improved versions of the bees algorithm for global optimisation\ Kamaruddin, Shafie
College : University of Birmingham
Date : 2018
student score : 2018
Degree : Thesis (Ph.D.)
Abstract : This research focuses on swarm-based optimisation algorithms, specifically the Bees Algorithm. The Bees Algorithm was inspired by the foraging behaviour of honey bees in nature. It employs a combination of exploration and exploitation to find the solutions of optimisation problems. This thesis presents three improved versions of the Bees Algorithm aimed at speeding up its operation and facilitating the location of the global optimum. For the first improvement, an algorithm referred to as the Nelder and Mead Bees Algorithm (NMBA) was developed to provide a guiding direction during the neighbourhood search stage. The second improved algorithm, named the recombination-based Bees Algorithm (rBA), is a variant of the Bees Algorithm that utilises a recombination operator between the exploited and abandoned sites to produce new candidates closer to optimal solutions. The third improved Bees Algorithm, called the guided global best Bees Algorithm (gBA), introduces a new neighbourhood shrinking strategy based on the best solution so far for a more effective exploitation search and develops a new bee recruitment mechanism to reduce the number of parameters. The proposed algorithms were tested on a set of unconstrained numerical functions and constrained mechanical engineering design problems. The performance of the algorithms was compared with the standard Bees Algorithm and other swarm based algorithms. The results showed that the improved Bees Algorithms performed better than the standard Bees Algorithm and other algorithms on most of the problems tested. Furthermore, the algorithms also involve no additional parameters and a reduction on the number of parameters as well.
Subject : TJ Mechanical engineering and machinery
Added Entry : University of Birmingham
کپی لینک

پیشنهاد خرید
پیوستها
عنوان :
نام فایل :
نوع عام محتوا :
نوع ماده :
فرمت :
سایز :
عرض :
طول :
ets742620_12585.pdf
ets742620.pdf
پایان نامه لاتین
متن
application/pdf
2.74 MB
85
85
نظرسنجی
نظرسنجی منابع دیجیتال

1 - آیا از کیفیت منابع دیجیتال راضی هستید؟