1 research outputs found
A decision support system for TV self-promotion scheduling
This paper describes a Decision Support System (DSS) that
aims to plan and maintain the weekly self-promotion space for
an over the air TV station. The self-promotion plan requires
the assignment of several self-promotion advertisements to a
given set of available time slots over a pre-specified planning
period. The DSS consists of a data base, a statistic module, an
optimization module, and a user interface. The input data is
provided by the TV station and by an external audiometry
company, which collects daily audience information. The
statistical module provides estimates based on the data
received from the audiometry company. The optimization
module uses a genetic algorithm that can find good solutions
quickly. The interface reports the solution and corresponding
metrics and can also be used by the decision makers to
manually change solutions and input data. Here, we report
mainly on the optimization module, which uses a genetic
algorithm (GA) to obtain solutions of good quality for
realistic sized problem instances in a reasonable amount of
time. The GA solution quality is assessed using the optimal
solutions obtained by using a branch-and-bound based
algorithm to solve instances of small size, for which
optimality gaps below 1% are obtained.This research had the support of COMPETE-FEDERPORTUGAL2020-POCI-NORTE2020-FCT funding via
grants POCI-01-0145-FEDER 031447 and 031821, NORTE-01-0145-FEDER-000020, and PTDC-EEI-AUT-2933-2014|16858–TOCCATA