scholarly journals Tire noise optimization problem: a mixed integer linear programming approach

Author(s):  
Matthias Becker ◽  
Nicolas Ginoux ◽  
Sébastien Martin ◽  
Zsuzsanna Roka

We present a Mixed Integer Linear Programming (MILP) approach in order to model the non-linear problem of minimizing the tire noise function. In a recent work, we proposed an exact solution for the Tire Noise Optimization Problem, dealing with an APproximation of the noise (TNOP-AP). Here we study the original non-linear problem modeling the EXact - or real - noise (TNOP-EX) and propose a new scheme to obtain a solution for the TNOP-EX. Relying on the solution for the TNOP-AP, we use a Branch&Cut framework and develop an exact algorithm to solve the TNOP-EX. We also take more industrial constraints into account. Finally, we compare our experimental results with those obtained by other methods.

2019 ◽  
Vol 61 (1) ◽  
pp. 64-75 ◽  
Author(s):  
HADI CHARKHGARD ◽  
ALI ESHRAGH

We study the problem of choosing the best subset of $p$ features in linear regression, given $n$ observations. This problem naturally contains two objective functions including minimizing the amount of bias and minimizing the number of predictors. The existing approaches transform the problem into a single-objective optimization problem. We explain the main weaknesses of existing approaches and, to overcome their drawbacks, we propose a bi-objective mixed integer linear programming approach. A computational study shows the efficacy of the proposed approach.


2014 ◽  
Vol 36 (7-8) ◽  
pp. 642-651 ◽  
Author(s):  
Julia Coelho Lemos ◽  
Bruna Carla Gonçalves Assis ◽  
André Luiz Hemerly Costa ◽  
Eduardo Mach Queiroz ◽  
Fernando Luiz Pellegrini Pessoa ◽  
...  

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