Ant Colony Optimization for the Film Production Scheduling Problem

• Main Authors: Kuan-Wei Chen, 陳冠瑋
• Other Authors: Ching-Jung Ting
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/t6452s

碩士 === 元智大學 === 工業工程與管理學系 === 106 === In film production, the cost of actors is one of the most important budgeting issues. In this study, we determine the sequence of the scenes of shooting days so that the total holding cost of actors’ and the total operating cost of the shooting days can be minimized. We also consider the daily working hours as the decision variable, which is defined as the total duration of scenes distributed in a single day. In this research, we develop a mixed integer programming model. Since the problem is NP-hard, we propose an Ant Colony Optimization (ACO) algorithm to solve the film production scheduling problem. A randomized variable neighborhood decent (RVND) is used as the local search approach to improve the solution. To access the effectiveness of the proposed ACO algorithm, we test three sets of benchmark instances from the literature. The first set includes 8 small sized instances. Our ACO can obtain all the optimal solutions. The second set has 240 instances. We can improve the best found solutions by up to 4.93%. The third set includes 1000 instances. We can found all best known solutions. The computational results indicate that of our ACO algorithm are able to provide good solutions within short computational times.