The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Mathematical Optimization by Using Particle Swarm Optimization, Genetic Algorithm, and Differential Evolution and Its Similarities
Abstract
To solve the problems of optimization, various methods are provided in different domain. Evolutionary computing (EC) is one of the methods to solve these problems. Mostly used EC techniques are available like Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolution (DE). These techniques have different working structure but the inner working structure is same. Different names and formulae are given for different task but ultimately all do the same. Here we tried to find out the similarities among these techniques and give the working structure in each step. All the steps are provided with proper example and code written in MATLAB, for better understanding. Here we started our discussion with introduction about optimization and solution to optimization problems by PSO, GA and DE. Finally, we have given brief comparison of these.
Related Content
|
Pawan Kumar, Mukul Bhatnagar, Sanjay Taneja.
© 2024.
26 pages.
|
|
Kapil Kumar Aggarwal, Atul Sharma, Rumit Kaur, Girish Lakhera.
© 2024.
19 pages.
|
|
Mohammad Kashif, Puneet Kumar, Sachin Ghai, Satish Kumar.
© 2024.
15 pages.
|
|
Manjit Kour.
© 2024.
13 pages.
|
|
Sanjay Taneja, Reepu.
© 2024.
19 pages.
|
|
Jaspreet Kaur, Ercan Ozen.
© 2024.
28 pages.
|
|
Hayet Kaddachi, Naceur Benzina.
© 2024.
25 pages.
|
|
|