Abstract:
Newspaper pagination has become an NP-hard
problem with the need to optimize the space of a newspaper.
A well paginated newspaper is a newspaper which includes a
high number of advertisements and articles along with
specific pagination rules. The research problem is to find an
efficient and suitable algorithm to generate a well paginated
newspaper. Most of the literature related to newspaper
pagination indicates the use of the Simulated Annealing
algorithm to solve the problem. In this research study, we
introduce an improved method of using the Genetic
Algorithm to solve the newspaper pagination problem along
with a method of deriving an improved solution using
Simulated Annealing. We use some heuristic methods within
the Genetic Algorithm and the Simulated Annealing
algorithm to achieve the basic pagination rules. This
research study includes a comparison of statistical data from
the two algorithms.
