@article{MAKHILLAJIT202019126820,
    title = {The Comparison Between Lofti-Cerveny-Weitz Method and Local Search Genetic Algorithm
for Completion of Maximally Diverse Grouping Problem},
    journal = {Asian Journal of Information Technology},
    volume = {19},
    number = {12},
    pages = {289-293},
    year = {2020},
    issn = {1682-3915},
    doi = {ajit.2020.289.293},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2020.289.293},
    author = {RZ,Arief and},
    keywords = {Maximally diverse grouping problem,Lofti-Cerveny-Weitz method local search,Genetic algorithm},
    abstract = {Maximally Diverse Grouping Problem
(MDGP) consists of grouping a set of M elements into G
groups. The diversity of the elements in each group is
maximized. The MDGP problem is one of the most
complex computational problems today. It is the NP-Hard
Problem. The Lofti-Cerveny-Weitz (LCW) method is a
variation of the Lofti-Cerveny (LC) method. It explains
that the search for element j is not limited to group g.
LCW considers all groups when searching for j element
except element i is located. Genetic algorithm is an
intelligent optimization technique based on simulations of
biological evolution. ZP Fan explains GA-based heuristic
steps combined with Local Search for MDGP. The
MDGP case of this study is at the ITERA dormitory. It
divided into several attributes. They are regional origin,
study programs, economics, religion and academic skills.
Moreover, they were classified into groups and every
group consisted of four students. Fitness value is
calculated by adding up all the distance of students in
each group. Student distance is obtained by using the
Euclidian distance formula at the distance of the five
student attributes. The result of this study showed that the
fitness value using the Lorent-Cerveny-Weitz method was
higher than the local search Genetic algorithm. It
explained that male dormitory were 0.0066 and
0.0011% for female dormitory. The computation time of
Lorent-Cerveny-Weitz Method was longer than the local
search Genetic algorithm. It explained that male
dormitory were 684 and 660% for female dormitory in
longer duration.}
    }