Date

2023-1-27

Author

Baran Tekin, Mehtap

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Movie scenes are not shot in the same order as they are shown in the movie. Scenes are shot independently in several distinct shooting sets with a set of actors, a film shooting crew, and several equipment as the resources. In shooting a film, several costs are incurred stemming from the usage of all these resources: wages of actors, fixed costs incurred due to hiring special shooting sets or sites, costs of using various resources like scenery, costumes and professional digital cameras, transfer costs of scenes, equipment, actors and shooting crew. Film producer companies pay the travel costs of actors to carry them to the shooting locations. However, in general, companies prefer to keep the actors in shooting sets and pay for them during their accommodation rather than covering the expensive mode of transportation. Actors are paid daily for both show-up days and do-not-show-up days while they are in shooting locations. In shooting a film, the film producer companies should consider many practical limitations such as precedence relationships among scenes, time periods indicating the earliest starting and latest completion times of scenes, and blocking time periods expressing the starting and ending of unavailability times of actors. Therefore, a movie scenes scheduling problem (MSSP) arises from the need for finding a feasible sequence of scenes and actors considering all limitations so as to minimize the total cost of shooting. In this study, the MSSP is defined by including the aforementioned operational limitations that have an essential effect on finding the optimal shooting schedule with the least cost possible. A mixed-integer linear programming (MILP) model is proposed, and a population-based metaheuristic, particle swarm optimization (PSO), is developed for the MSSP. Finally, the performances of the MILP model and PSO algorithm are analysed with several problem instances of different sizes and also a real script.

Subject Keywords

Movie Scenes Scheduling, Discrete Particle Swarm Optimization Algorithm, Mixed-Integer Linear Programming

URI

https://hdl.handle.net/11511/102766

Collections

Graduate School of Natural and Applied Sciences, Thesis