Results 211 to 220 of about 12,060 (243)

A reliable mixed-integer linear programming formulation for data-driven model predictive control in buildings. [PDF]

MethodsX
Klanatsky P, Veynandt F, Heschl C.
europepmc   +1 more source

Integer programming for learning directed acyclic graphs from nonidentifiable Gaussian models. [PDF]

Biometrika
Xu T, Taeb A, Küçükyavuz S, Shojaie A.   +3 more
europepmc   +1 more source

Data-Driven Chance Constrained Mixed Integer Nonlinear Bilevel Optimization via Copulas. [PDF]

Ind Eng Chem Res
Johnn SN, Nikkhah H, Tsai ML, Avraamidou S, Beykal B, Charitopoulos VM.   +5 more
europepmc   +1 more source

Mathematical formulations and a Relax-and-Fix heuristic algorithm for capacitated reliable fixed-charge facility location problems. [PDF]

J Heuristics
Roshani A, Parry G, Walker-Davies P.
europepmc   +1 more source

Optimizing sustainable hub depot locations for empty container logistics in Slovenia using particle swarm optimization. [PDF]

Sci Rep
Tuljak-Suban D.
europepmc   +1 more source

Enabling continuous 24/7 vertical mobility in High-Rise buildings by integrating critical activity scheduling and night shift planning. [PDF]

Sci Rep
Ahmadnia M, Maghrebi M, Khodatars F.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Decomposition Branching for Mixed Integer Programming

Operations Research, 2022
Applications of mixed integer programming can be found in many industries, such as transportation, healthcare, energy, and finance, and their economic impact is significant. It is also well known that mixed integer programs (MIPs) can be very difficult to solve.
Baris Yildiz 0001, Natashia Boland, Martin W. P. Savelsbergh   +2 more
openaire   +3 more sources

Presolve Reductions in Mixed Integer Programming

INFORMS Journal on Computing, 2020
Mixed 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, Robert E. Bixby, Zonghao Gu, Edward Rothberg, Dieter Weninger   +4 more
openaire   +2 more sources

Mixed-integer programming for control

Proceedings of the 2005, American Control Conference, 2005., 2005
The article describes how mixed-integer programming (MIP) can be employed for feedback control. MIP can be used to find optimal trajectories subject to integer constraints, which can encode discrete decisions or nonconvexity, for example. This optimization can be performed online within model predictive control (MPC) to implement a feedback control law.
Richards, AG, How, JP
openaire   +1 more source

Structure Detection in Mixed-Integer Programs

INFORMS Journal on Computing, 2018
Despite vast improvements in computational power, many large-scale optimization problems involving integer variables remain difficult to solve. Certain classes, however, can be efficiently solved by exploiting special structure. One such structure is the singly bordered block-diagonal (BBD) structure that lends itself to Dantzig-Wolfe decomposition ...
Taghi Khaniyev, Samir Elhedhli, Fatih Safa Erenay   +2 more
openaire   +1 more source