In this paper, we integrate goal programming (GP), Taylor Series, Kuhn-Tucker conditions and Penalty Function approaches to solve linear fractional bi-level programming (LFBLP)problems. As we know, the Taylor Series is having the property of transforming fractional functions to a polynomial. In the present article by Taylor Series we obtain polynomial objective functions which are equivalent...

multi objective quadratic fractional programming (moqfp) problem involves optimization of several objective functions in the form of a ratio of numerator and denominator functions which involve both contains linear and quadratic forms with the assumption that the set of feasible solutions is a convex polyhedral with a nite number of extreme points and the denominator part of each of the object...

Benchmarking plays a crucial role in both development of new optimization methods, and conducting proper comparisons between already existing particularly the field evolutionary computation. In this paper, we develop benchmark functions for bound-constrained single-objective that are based on zigzag function. The proposed function has three parameters control its behaviour difficulty resulting ...

Abstract Molecular simulations are a powerful tool to complement and interpret ambiguous experimental data on biomolecules obtain structural models. Such data-assisted often rely parameters, the choice of which is highly non-trivial crucial performance. The key challenge weighting information with respect underlying physical model. We introduce FLAPS, self-adapting variant dynamic particle swar...

ABSTRACT: The problem of robust design is treated as a bi-objective optimization problem in which the performance mean and variation are optimized and minimized, respectively. A method for deriving a utility function as a local approximation of the efficient frontier is presented and investigated at different locations of candidate solutions, with different ranges of interest, and for efficient...