A bounded polyhedron is sometimes called a polytope, but some authors use the opposite convention (i.e., polytope for any set of the form 2.5, and polyhedron when it is bounded.) 虽然不太清楚那两词的区别,但是根据这句话能够
Linear programming problem is widely applied in engineering group. And artificial neural network is an effective and practical method and approach for solving linear programming problem of nonlinear convex set constraints in engineering field. Most models of artificial neural network are nonlinear dynamic ...
第3讲 凸集、凸函数、凸规划 凸性(Convexity)是最优化理论必须涉及到基本概念.具有凸性的非线性规划模型是一类特殊的重要模型，它在最优化的理论证明及算法研究中具有非常重要的作用. 凸集(ConvexSet)凸函数(ConvexFunction)凸规划(ConvexProgramming) 线性组合(linearCombination)mnixi,其中iR...
It is shown that this problem, which is still open even in dealing with general convex regions, is exactly equivalent to a set of linear algebraic equalities/inequalities in mixed real‐integer variables, which can be solved efficiently by using the available software. Application of the proposed...
eralizedlinearprogrammingtechniques,ornumericallybygeneralizedgradientdescenttechniques. Inthispaperwesurveyquasiconvexprogrammingalgorithmsandapplications. 1.1QuasiconvexFunctions LetYbeatotallyorderedset,forinstancetherealnumbersRorintegersZorderednumerically. Foranyfunctionf:X →Y,andanyvalueλ∈Y,wedefinethelowerle...
We recall that in linear programming small continuous changes of data can cause discontinuities, such as a sudden collapse or an explosion of the feasible set. This typically results in jumps of optimal solutions and the optimal value. The main objective of the report is to suggest a method ...
The set of points for which the objective and all constraint functions are defined: (0.2)D:=⋂i=0mdomfi∩⋂j=1pdomhj is called the domain of the optimization problem (0.1) . A point x∈D is feasible, if it satisfies all the inequality and equality constraints. The set which cont...
Fixed variables are set through lb(*)=ub(*). Equality constraints may be linear dependent and they are checked against incompatibilty. The cpu time is similar to quadprog and precision is usually better in particular for ill conditionned problem. The package has been written with matlab R2018a...
1992) for the training set X.the hypothesis space consists of linear functions, thenthese problems can be solved using linear program-ming, least-squares regression, and support vector ma-chines respectively. These are all examples of convexprogramming problems.IfConvex programming has other applicatio...
convex programming Acronyms [′kän‚veks ′prō‚gram·iŋ] (mathematics) Nonlinear programming in which both the function to be maximized or minimized and the constraints are appropriately chosen convex or concave functions of the independent variables. ...