Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
7-2014
Abstract
We address the problem of minimizing staffing cost in a contact center subject to service level requirements over multiple weeks. We handle both the capacity planning and agent schedule generation aspect of this problem. Our work incorporates two unique business requirements. First, we develop techniques that can provide near-optimal staffing for 247 contact centers over long term, upto eight weeks, rather than planning myopically on a week-on-week basis. Second, our approach is usable in an online interactive setting in which staffing managers using our system expect high quality plans within a short time period. Results on large real world and synthetic instances show that our Lagrangian relaxation based technique can achieve a solution within 94% of optimal on an average, for eight week problems within ten minutes, whereas a generic integer programming solver can only achieve a solution within 80% of optimal. Our approach is also deployed in live business environment and reduces headcount by a decile over techniques used previously by our client business units.
Keywords
contact center, planning and scheduling
Discipline
Artificial Intelligence and Robotics | Management Information Systems
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 24th International Conference on Automated Planning and Scheduling: Portsmouth, NH, 21-26 June 2014
First Page
395
Last Page
403
ISBN
9781577356608
Publisher
AAAI Press
City or Country
Palo Alto, CA
Citation
KUMAR, Akshat; SINGH, Sudhanshu; GUPTA, Pranav; and PARIJA, Gyana.
Near-Optimal Nonmyopic Contact Center Planning using Dual Decomposition. (2014). Proceedings of the 24th International Conference on Automated Planning and Scheduling: Portsmouth, NH, 21-26 June 2014. 395-403.
Available at: https://ink.library.smu.edu.sg/sis_research/2196
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.aaai.org/ocs/index.php/ICAPS/ICAPS14/paper/view/7902