  Tabu Search (TS) metaheuristic improves simple local search algorithms (e.g.
steepest ascend hill-climbing) by enabling the algorithm to escape local optima
points. It has shown to be useful for addressing several combinatorial
optimization problems. This paper investigates the performance of TS and
considers the effects of the size of the Tabu list and the size of the
neighbourhood for a procedural content generation, specifically the generation
of maps for a popular tabletop game called Terra Mystica. The results validate
the feasibility of the proposed method and how it can be used to generate maps
that improve existing maps for the game.
