Integer programming techniques for solving non-linear workforce planning models with learning

Mike Hewitt; Austin Chacosky; Scott E. Grasman; Barrett W. Thomas

doi:10.1016/j.ejor.2014.10.060

Integer programming techniques for solving non-linear workforce planning models with learning

Mike Hewitt, Austin Chacosky, Scott E. Grasman, Barrett W. Thomas

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	942-950
Number of pages	9
Journal	European Journal of Operational Research
Volume	242
Issue number	3
DOIs	https://doi.org/10.1016/j.ejor.2014.10.060
State	Published - May 1 2015
Externally published	Yes

ASJC Scopus Subject Areas

General Computer Science
Modeling and Simulation
Management Science and Operations Research
Information Systems and Management

Keywords

Human learning
Nonlinear programming
Production planning and scheduling

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10.1016/j.ejor.2014.10.060

Cite this

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title = "Integer programming techniques for solving non-linear workforce planning models with learning",

keywords = "Human learning, Nonlinear programming, Production planning and scheduling",

author = "Mike Hewitt and Austin Chacosky and Grasman, {Scott E.} and Thomas, {Barrett W.}",

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language = "English",

volume = "242",

pages = "942--950",

journal = "European Journal of Operational Research",

issn = "0377-2217",

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AU - Hewitt, Mike

AU - Chacosky, Austin

AU - Grasman, Scott E.

AU - Thomas, Barrett W.

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KW - Human learning

KW - Nonlinear programming

KW - Production planning and scheduling

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DO - 10.1016/j.ejor.2014.10.060

M3 - Article

AN - SCOPUS:84920520636

SN - 0377-2217

VL - 242

SP - 942

EP - 950

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 3

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Integer programming techniques for solving non-linear workforce planning models with learning

ASJC Scopus Subject Areas

Keywords

Access to Document

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