The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
An Object-Oriented Framework for Rapid Genetic Algorithm Development
Abstract
JGA, the acronym for Java Genetic Algorithm, is a computational object-oriented framework for rapid development of evolutionary algorithms for solving complex optimization problems. This chapter describes the JGA framework and illustrates its use on the dynamic inventory lot-sizing problem. Using this problem as benchmark, JGA is compared against three other tools, namely, GAlib, an open C++ implementation; GADS, a commercial MatlabÒ toolbox; and PROC GA, a commercial (yet experimental) SASÒ procedure. JGA has proved to be a flexible and extensible object-oriented framework for the fast development of single (and multi-objective) genetic algorithms by providing a collection of ready-to-use modules (Java classes) that comprise the nucleus of any genetic algorithm. Furthermore, JGA has also been designed to be embedded in larger applications that solve complex business problems.
Related Content
|
S. Karthigai Selvi, Sharmistha Dey, Siva Shankar Ramasamy, Krishan Veer Singh.
© 2025.
16 pages.
|
|
S. Sheeba Rani, M. Mohammed Yassen, Srivignesh Sadhasivam, Sharath Kumar Jaganathan.
© 2025.
22 pages.
|
|
U. Vignesh, K. Gokul Ram, Abdulkareem Sh. Mahdi Al-Obaidi.
© 2025.
22 pages.
|
|
Monica Bhutani, Monica Gupta, Ayushi Jain, Nishant Rajoriya, Gitika Singh.
© 2025.
24 pages.
|
|
U. Vignesh, Arpan Singh Parihar.
© 2025.
34 pages.
|
|
Sharmistha Dey, Krishan Veer Singh.
© 2025.
20 pages.
|
|
Kalpana Devi.
© 2025.
26 pages.
|
|
|