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This book is the first work dedicated to the Bees Algorithm. Following a gentle introduction to the main ideas underpinning the algorithm, the book presents recent results and developments relating to the algorithm and its application to optimisation problems in production and manufacturing.
With the advent of the Fourth Industrial Revolution, production and manufacturing processes and systems have become more complex. To obtain the best performance from them requires efficient and effective optimisation techniques that do not depend on the availability of process or system models. Such models are usually either not obtainable or mathematically intractable due to the high degrees of nonlinearities and uncertainties in the processes and systems to be represented. The Bees Algorithm is a powerful swarm-based intelligent optimisation metaheuristic inspired by the foraging behaviour of honeybees. The algorithm is conceptually elegant and extremely easy to apply. All it needs to solve an optimisation problem is a means to evaluate the quality of potential solutions.
The Bees Algorithm may be considered a form of Swarm Optimisation (SO) algorithm in that it is a method inspired by the collective behaviour exhibited by animals. SO algorithms are inspired by groups of animals that gather in a particular area (often in large numbers), for instance, flocking of birds or the schooling of fish. In particle SO systems, there exists a population of candidate solutions within which individual solutions take the form of “particles” that will evolve or alter positions. The specific positions of the particles in a search space are self-adjusted based upon the experience of the particle and that of neighbouring particles by recalling the best location visited by the particle and its neighbours, therefore applying local and global search methods together.
The Bees Algorithm is based specifically on the behaviour of the common honeybee and its original and basic form, which is described in detail and developed by Pham et al., to solve the continuous optimisation problem that involves randomly generating scout bees within the search space of the target function for optimisation, followed by an evaluation of the fitness of the sites within the search space that were visited by scout bees. The method for the evaluation of fitness is dependent on the problem to be optimised. However, in general, the ‘fitness’ can be the output value of a function that is to be optimised.
This book demonstrates the simplicity, effectiveness and versatility of the algorithm and encourages its further adoption by engineers and researchers across the world to realise smart and sustainable manufacturing and production in the age of Industry 4.0 and beyond.
The Bees Algorithm—A Gentle Introduction
Minimising Printed Circuit Board Assembly Time Using the Bees Algorithm with TRIZ-Inspired Operators
The application of the Bees Algorithm in a Digital Twin for Optimising the Wire Electrical Discharge Machining (WEDM) Process Parameters
A Case Study with the BEE-Miner Algorithm: Defects on the Production Line
An Application of the Bees Algorithm to Pulsating Hydroforming
Shape Recognition for Industrial Robot Manipulation with the Bees Algorithm
Bees Algorithm Models for the Identification and Measurement of Tool Wear
Global Optimisation for Point Cloud Registration with the Bees Algorithm
Automatic PID Tuning Toolkit Using the Multi-Objective Bees Algorithm
The Effect of Harmony Memory Integration into the Bees Algorithm
A Parallel Multi-indicator-Assisted Dynamic Bees Algorithm for Cloud-Edge Collaborative Manufacturing Task Scheduling