
Evolutionary Computation in Scheduling
Wiley-Blackwell (Publisher)
1st Edition
Published on 8. May 2020
Book
Hardback
368 pages
978-1-119-57384-5 (ISBN)
Description
Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems
This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches.
Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book:
* Provides a representative sampling of real-world problems currently being tackled by practitioners
* Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence
* Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems
Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.
More details
Language
English
Place of publication
Hoboken
United States
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Dimensions
Height: 206 mm
Width: 147 mm
Thickness: 18 mm
Weight
227 gr
ISBN-13
978-1-119-57384-5 (9781119573845)
Schweitzer Classification
Other editions
Additional editions

Amir H. Gandomi | Ali Emrouznejad | Mo M. Jamshidi
Evolutionary Computation in Scheduling
E-Book
04/2020
1st Edition
Wiley
€108.99
Available for download

Amir H. Gandomi | Ali Emrouznejad | Mo M. Jamshidi
Evolutionary Computation in Scheduling
E-Book
04/2020
1st Edition
Wiley
€108.99
Available for download
Persons
Amir H. Gandomi, PhD, is Professor of Data Science at University of Technology Sydney, Australia.
Ali Emrouznejad, PhD, is Professor and Chair of Business Analytics at Aston University, UK.
Mo M Jamshidi, PhD, is Lutcher Brown Endowed Chair and Professor of Electrical and Computer Engineering at the University of Texas at San Antonio, USA.
Kalyanmoy Deb, PhD, is Koenig Endowed Chair and Professor of Electrical and Computer Engineering at Michigan State University, USA.
Iman Rahimi, PhD, is a member of the Young Researchers and Elite Club, Isfahan (Khorasgan) Branch at Islamic Azad University, Iran.
Editor
University of Technology Sydney, Australia
Aston University, UK
University of Texas at San Antonio, USA
Content
Evolutionary Computation in Scheduling: A Scientometric Analysis 1
Amir H. Gandomi, Ali Emrouznejad, Iman Rahimi
Role and Impacts of Ant Colony Optimization in Job Shop Scheduling Problems: A Detail Analysis 8
P.Deepalakshmi, K. Shankar
Advanced Ant Colony Optimization in Healthcare Scheduling 35
Reza Behmanesh, Iman Rahimi, Mostafa Zandieh, Amir H. Gandomi
Task Scheduling in Heterogeneous Computing Systems using Swarm Intelligence 65
S Sarathambekai, K Umamaheswari
Computationally Efficient Scheduling Schemes for Multiple Antenna Systems Using Evolutionary Algorithm and Swarm Optimization 85
Prabina Pattanayak, Preetam Kumar
An Efficient Modified Red Deer Algorithm to Solve a Truck Scheduling Problem Considering Time Windows and Deadline for Trucks' Departure 127
Amir Mohammad Fathollahi-Fard, Abbas Ahmadi, Mohsen S. Sajadieh
Application of Sub-Population Scheduling Algorithm in Multi-Population Evolutionary Dynamic Optimization 150
Javidan Kazemi Kordestani, Mohammad Reza Meybodi
Task Scheduling in Cloud Environments: A Survey on Population-Based Evolutionary Algorithms 193
Fahimeh Ramezani, Mohsen Naderpour, Javid Taheri, Jack Romanous, Albert Y. Zomaya
Scheduling of Robotic Disassembly in Remanufacturing using Bees Algorithm 228
Jiayi Liu, Wenjun Xu, Zude Zhou, Duc Truong Pham
A Modified Fireworks Algorithm to solve the Heat and Power Generation Scheduling Problem in Power System Studies 272
Mohammad Sadegh Javadi, Ali Esmaeel Nezhad, Seyed-Ehsan Razavi, Abdollah Ahmadi, João P. S. Catalão