Talent scheduling with daily working capacity and scene changeover times

This paper investigates a talent scheduling problem that incorporates daily work capacity constraints and the changeover times between consecutive scenes filmed on the same day. The problem inherently integrates three key optimization challenges: talent scheduling, the traveling salesperson problem,...

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Bibliographic Details
Published in:Omega (Oxford) Vol. 138; p. 103439
Main Authors: Yang, Zhaoqi, Tanaka, Shunji, Lin, Bertrand M.T.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.01.2026
Subjects:
Changeover time
Daily capacity
Dynamic programming
Integer linear program
Talent scheduling
Daily capacity
Talent scheduling
Integer linear program
Dynamic programming
Changeover time
ISSN:0305-0483
Online Access:Get full text
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Summary:This paper investigates a talent scheduling problem that incorporates daily work capacity constraints and the changeover times between consecutive scenes filmed on the same day. The problem inherently integrates three key optimization challenges: talent scheduling, the traveling salesperson problem, and bin packing. To obtain an optimal solution, we develop two integer linear programming models and a dynamic programming algorithm. Additionally, we introduce a polynomial-time dynamic programming algorithm for the special case where the filming order of all scenes is predetermined. This polynomial-time algorithm is incorporated into a tabu search framework to generate high-quality approximate solutions. Finally, we conduct a computational study to assess the effectiveness and efficiency of all proposed solution approaches. The approach of simplifying the problem structures significantly outperforms other algorithms in solution quality and execution time for large-scale instances. •Formulate talent scheduling with daily working capacity and scene changeover times.•Propose two integer linear programs.•Design two dynamic programming algorithms.•Design a hybrid algorithm with a dynamic program and tabu search.•Conduct a computational study.
ISSN:0305-0483
DOI:10.1016/j.omega.2025.103439