[PDF] Top 20 Optimization problems for set functions

... mization problems, namely the problems of finding conditional extrema of set func- ...of problems has been shown to arise in interval and pointwise estima- tion of probability distribution, ... See full document

... of optimization problems with set functions is ...optimal problems can be transformed to standard mixed problems of mathe- matical programming in Euclidean ...these ... See full document

... Quasi variational inequality ( QVI ) problems started with a pioneer work of Bensoussan and Lions in 1973. The terminology quasi variational inequality was coined by Bensoussan et al. [3]. A QVI QVI is an ... See full document

... vector optimization problems in Banach ...vector optimization problem and the vector variational-like inequality involving set-valued ...vector optimization problems by using the ... See full document

... vector optimization the- ...vector optimization problems with set-valued maps in general spaces and derived scalarization results, -saddle point theorems, and - duality assertions using ... See full document

... traditional optimization algorithms often depend on the quality of the objective function, but many objective functions are usually highly non-linear, steep, multi-peak, non-differential or even ... See full document

... swarm optimization (PSO) to solve complex variable fractional programming problems (CVFPP) where the objective function includes the two parts (real and imaginary), the input is complex while the output is ... See full document

... multiobjective optimization on permutations (MOP) is offered based on the Directed Structuring Method and using Graph ...multiobjective optimization on permutations and multi-permutations. Most ... See full document

... convex set such that Ω ⊆ ...convergent) optimization algorithms have been developed for (1) when f is smooth and/or strongly ...convex optimization problems, which have many ap- plications in ... See full document

... The result of [14] is also extended in [15] by considering locally Lipschitz functions, Fréchet differentiable equality constraints, and an abstract set constraint. These authors establish the KT ... See full document

... Multi-Objective Optimization (MOO) techniques often achieve the combina- tion of both maximization and minimization ...multi-objective functions simpler using duality. An example of four objective ... See full document

... colony optimization is a technique for optimization that was introduced in the early ...colony optimization is the foraging behaviour of real ant ...discrete optimization problems, to ... See full document

... multiple-objective optimization problems to evaluate the effectiveness of spherical ...multiple-objective optimization, and the other was a real-life diesel engine fuel injection scheduling ...lution ... See full document

... a set of mathematical equations which provides a well-ordered computational means to predict the state of a process, and also it minimizes the mean of the squared ... See full document

... related optimization problems; see [4, 19, 20, 21, 22, 23, 24, ...merit functions for mixed quasivariational ...merit functions for mixed quasivariational inequalities and use these merit ... See full document

... convex optimization problems, and correspond to the particular case of the convex set being the intersection of an affine family of matrices and the pos- itive semidefinite ... See full document

... global optimization problems of multi-minima functions with ...a set of benchmark multimodal functions whose global and local minima are ...the optimization of fiber grating ... See full document

... section. Optimization of the surrogate objective functions was conducted with the multi- island genetic algorithm in iSIHT ...was set to run for 200,000 total objective-function evaluations. ... See full document

... stability set of the first kind for MONLP with fuzzy parameters in both the objective functions and the constraints without any differentiability ...stability set of the first kind of such ... See full document

... studied optimization problems involving set- valued maps using generalized convexity concepts with good stability properties which are helpful in order to write optimality conditions for the studied ... See full document