This is my solution to one of the questions of the TASA Challenge pre-selection stage. The complete test can be found here.
The translated question (made by DeepL) is the following:
Today is the annual Data Science conference and will be attended by 8 speakers from different software brands. The past few times that the conference has been organized there has been a lot of tension between speakers, discussions and all kinds of conflicts. This year, it has been determined that an algorithm will be used to locate speakers in order to reduce conflicts. To do this, the information from past conferences was digitized, a conflict indicator (CI) was determined based on the frequency and severity of discussions between speakers, and everything was compiled into the file within the '
Data' folder called 'speakers.txt' The task is to determine the optimal location of the speakers, assuming they will be seated at a round table, as well as the minimized value of the total CI (the sum of all the CIs).
The 'speakers.txt' file was also translated by me.
The original question (in spanish) is the following:
Hoy es la conferencia anual de Data Science y asistirán 8 expositores de distintas marcas de software. Las veces pasadas que se ha organizado la conferencia ha habido mucha tensión entre expositores, discusiones y todo tipo de conflictos. Este año, se ha determinado que se utilizará un algoritmo para ubicar a los expositores de manera que se reduzcan los conflictos. Para esto, se digitalizó la información de las conferencias pasadas, se determinó un indicador de conflictos (IDC) en función a la frecuencia y gravedad de las discusiones entre expositores, y se recopiló todo en el archivo dentro de la carpeta '
Data' llamado 'speakers.txt'. La tarea consiste en determinar la ubicación óptima de los expositores, asumiendo que estarán sentados en una mesa redonda, así como el valor minimizado del IDC total (la suma de todos los IDC).