A makespan minimization problem for versatile developers in the game industry

Abstract

Today, the development of a modern video game draws upon multiple areas of expertise. Moreover, its development cost could be as high as tens of millions of dollars. Consequently, we should carefully schedule its jobs so as not to increase the total cost. However, project leaders traditionally treat developers alike or even schedule all the jobs manually. In this study, we consider a versatile-developer scheduling problem. The objective is to minimize the makespan of a game project. We propose a branch-and-bound algorithm (B&B) to generate the optimal schedules for small problem instances. On the other hand, an imperialist competitive algorithm (ICA) is proposed to obtain approximate schedules for large problem instances. Lastly, computational experiments are conducted to show the performances of both algorithms. When the problem size is small (e.g.= 12), B&B can generate the optimal schedules within 5 s. For some large problem instances (e.g., = 600), near-optimal schedules can be obtained by ICA within 10 min. The final results imply that both algorithms converge quickly and are of high solution quality.