Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study. [PDF]
Renggli FJ +4 more
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Abstract Background and aims The impact of exposure to cannabis dispensaries on young adult cannabis use may depend on how exposures and outcomes are defined. We estimated associations of dispensary exposure with young adult cannabis use across: (a) a government‐maintained licensed dispensaries registry versus a web‐scraped list of licensed and ...
Alyssa F. Harlow +9 more
wiley +1 more source
A linear programming framework for optimizing molecular combinations of asphalt four components. [PDF]
Zhu J, Wen C, Tao S.
europepmc +1 more source
Data-Driven Chance-Constrained Mixed Integer Nonlinear Bi-level Optimisation Via Copulas: Application To Integrated Planning And Scheduling Problems. [PDF]
Johnn SN +5 more
europepmc +1 more source
Distributed decision-making in a shared power network: a game-theoretic framework for integrated electricity and gas systems. [PDF]
Huang J, Yu T, Pan Z, Wu Y.
europepmc +1 more source
Multi-objective optimization of a regional biogas supply chain using organic waste. [PDF]
Malashin IP +5 more
europepmc +1 more source
IGM: Integrated Gene-expression Modeling for multi-condition flux-preserving genome-scale metabolic models. [PDF]
Paklao T, Suratanee A, Plaimas K.
europepmc +1 more source
Optimizing Cold Food Supply Chains for Enhanced Food Availability Under Climate Variability. [PDF]
Hernandez-Cuellar D +2 more
europepmc +1 more source
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Presolve Reductions in Mixed Integer Programming
INFORMS Journal on Computing, 2020Mixed integer programming has become a very powerful tool for modeling and solving real-world planning and scheduling problems, with the breadth of applications appearing to be almost unlimited. A critical component in the solution of these mixed integer programs is a set of routines commonly referred to as presolve.
Tobias Achterberg +4 more
openaire +4 more sources
Mixed-Integer Linear Programming Formulations
2014In this chapter, (mixed-)integer linear programming formulations of the resource-constrained project scheduling problem are presented. Standard formulations from the literature and newly proposed formulations are classified according to their size in function of the input data.
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