Free shipping on all orders over $79* Limited Time Only
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Initialization and Diversity in Optimization Algorithms - Diego Oliva

Initialization and Diversity in Optimization Algorithms

By: Diego Oliva, Marco Antonio Perez Cisneros, Bernardo Morales-Castañeda, Mario A. Navarro Velázquez

eText | 19 February 2026 | Edition Number 1

At a Glance

eText

$291.50

or 4 interest-free payments of $72.88 with

 or 

Available: 19th February 2026

Preorder. Online access available after release.

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

Designing new algorithms in swarm intelligence is a complex undertaking. Two critical factors have been seen to have a direct correlation with positive results. First is initialization, which serves as the initial step for all swarm intelligence techniques. Candidate solutions are generated to form the initial population, which are subsequently modified during the iterative process. A well-initialized population increases the algorithm's chances of avoiding local optima and finding the global optimum in fewer iterations. Although random distributions are commonly used for initialization, there are various ways to initialize the population elements.

Maintaining diversity among the population elements throughout the iterative process is also essential. This diversity facilitates a more thorough and efficient exploration of the search space. In swarm intelligence algorithms, there are multiple methods to measure diversity, each with its own advantages and disadvantages.

This book presents the theory behind the initialization process and the different mechanisms. Additionally, it includes a comparative study of various diversity indicators. It explores different methodologies to compute its value and explains how it can be incorporated as a mechanism for deciding when to apply operators during the optimization process. Multiple examples are provided in the book using two classical algorithms: Differential Evolution and Particle Swarm Optimization. It includes MATLAB® code and offers several exercises that readers can use for experimentation and design purposes.

on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionMathematicsApplied MathematicsComputing & I.T.Computer ScienceArtificial IntelligenceSystems Analysis & DesignEngineering & TechnologyMechanical Engineering & MaterialsProduction & Industrial EngineeringOptimisationEnergy Technology & Engineering
Electrical EngineeringElectronics & Communications EngineeringElectronics EngineeringAutomatic Control EngineeringProbability & Statistics

More in Computer Science

Amazon.com : Get Big Fast - Robert Spector

eBOOK

Amazon.com

Get Big Fast

eBook

$22.99

This is For Everyone - Tim Berners-Lee

eBOOK

This is For Everyone

eBook

$17.99

This product is categorised by