Methods, systems, and apparatus, including computer programs encoded on computer storage media, for solving mixed integer programs (MIPs) using neural networks. One of the methods includes obtaining data specifying parameters of a MIP; generating, from the parameters of the MIP, an input ...
Solving Mixed Integer Programs Using Neural Networks 来自 arXiv.org 喜欢 0 阅读量: 765 作者:V Nair,S Bartunov,F Gimeno,IV Glehn,Y Zwols 摘要: Mixed Integer Programming (MIP) solvers rely on an array of sophisticated heuristics developed with decades of research to solve large-scale MIP ...
Mahajan, A.: Presolving mixed-integer linear programs. In: Cochran, J.J., Cox, L.A., Keskinocak, P., Kharoufeh, J.P., Smith, J.C. (eds.) Wiley Encyclopedia of Operations Research and Management Science, pp. 4141–4149. Wiley, New York (2010) Google Scholar Mahajan, A., Leyffer...
to analyze Pyomo models, interfaces to well-known linear, mixed-integer, and non- linear solvers, and provides an architecture that supports parallel solver execution. Coopr also includes an installation utility that automatically installs the diverse set ...
The initial problem, which was a mixed integer non-linear programming (MINLP) problem, was decomposed into two sub-problems—optimal spectrum sensing, and opti- mal channel assignment and power allocation—without sacrificing optimality. The advantage of this solution technique is the possibility of ...
Besides, more investigation regarding using “deep” structures, which can make neural networks exhibit the local approximation property, is suggested. Apart from the neural network, it is also of significance to explore the initialisation schemes that can enhance the local approximation property of ...
Neural network (NN) technique.In this paper, we discuss non-linear mixed integer programming (NMIP) models which should be simultaneously determined continuous and discrete decision variables. This problem is more difficult than the NIP problem while more actually representing the real world. Recently...
The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems,...
Hence, the position of each bobcat represents a candidate solution to the problem, which can be modeled from a mathematical point of view using a vector, where each element of this vector represents a decision variable. Together, bobcats form the population of the algorithm, which can be ...
In this paper, we propose a new method in which a neural network technique is hybridized with genetic algorithms for solving nonlinear integer programming problems. The hybrid GA is employed the simpelx search method, and the chromosomes are improved to good points by using the simplex search ...