Solving Talent Scheduling with Dynamic Programming-Reference-Cited by-同舟云学术

Solving Talent Scheduling with Dynamic Programming

Published:2011-02 Issue:1 Volume:23 Page:120-137
ISSN:1091-9856
Container-title:INFORMS Journal on Computing
language:en
Short-container-title:INFORMS Journal on Computing

Author:

Garcia de la Banda Maria,Stuckey Peter J.,Chu Geoffrey

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

General Engineering

Link

https://pubsonline.informs.org/doi/pdf/10.1287/ijoc.1090.0378

Reference18 articles.

1. A Dynamic Programming Formulation with Diverse Applications

2. Ambühl C., Mastrolilli M., Svensson O. Inapproximability results for sparsest cut, optimal linear arrangement, and precedence constrained schedulingProc. 48th Annual IEEE Sympos. Foundations Comput. Sci.(2007) Washington, DCIEEE329337

3. A method for solving the minimization of the maximum number of open stacks problem within a cutting process

4. Optimal scheduling in film production to minimize talent hold cost

5. Chu G., Stuckey P. J., Gent I. Minimizing the maximum number of open stacks by customer searchProc. 15th Internat. Conf. Principles and Practice of Constraint Programming(2009) 5732BerlinSpringer242257Lecture Notes in Computer Science

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Lower bounds for minimizing two types of unnecessary costs in the film and television industry;Computers & Operations Research;2024-10

2. A Quantum Annealing-Based Approach for Solving Talent Scheduling;2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA);2024-02-01

3. Automatic generation of dominance breaking nogoods for a class of constraint optimization problems;Artificial Intelligence;2023-10

4. An Iterated Local Search for the Talent Scheduling Problem with Location Costs;2022 14th International Conference on Knowledge and Systems Engineering (KSE);2022-10-19

5. A Study of Transfer Learning in an Ant-Based Generation Construction Hyper-Heuristic;2022 IEEE Congress on Evolutionary Computation (CEC);2022-07-18