Duc Truong Pham, Hartono N. Intelligent Production and Manufacturing Optimisation-The Bees Algorithm Approach

Springer, 2023. — 396 p.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 optimization problems in production and manufacturing.With the advent of the Fourth Industrial Revolution, production and manufacturing processes and systems have become more complex. Obtaining the best performance from them requires efficient and effective optimization 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 optimization metaheuristic inspired by the foraging behavior of honeybees. The algorithm is conceptually elegant and extremely easy to apply. All it needs to solve an optimization problem is a means to evaluate the quality of potential solutions.The Bees Algorithm may be considered a form of Swarm Optimization (SO) algorithm in that it is a method inspired by the collective behavior exhibited by animals. SO algorithms are inspired by groups of animals that gather in a particular area (often in large numbers), for instance, the 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 neighboring particles by recalling the best location visited by the particle and its neighbors, therefore applying local and global search methods together.The Bees Algorithm is based specifically on the behavior 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 optimization problem that involves randomly generating scout bees within the search space of the target function for optimization, 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 optimized. However, in general, the ‘fitness’ can be the output value of a function that is to be optimized.This book demonstrates the simplicity, effectiveness, and versatility of the algorithm and encourages its further adoption by engineers and researchers across the world to realize smart and sustainable manufacturing and production in the age of Industry 4.0 and beyond.The Bees Algorithm — A Gentle Introduction.
Minimizing Printed Circuit Board Assembly Time Using the Bees Algorithm with TRIZ-Inspired Operators.
The application of the Bees Algorithm in a Digital Twin for Optimizing 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 Optimization 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.