نتایج جستجو برای: objective optimization

تعداد نتایج: 838672  

Journal: :Neural Computing and Applications 2023

Abstract The Chaos Game Optimization (CGO) has only recently gained popularity, but its effective searching capabilities have a lot of potential for addressing single-objective optimization issues. Despite advantages, this method can tackle problems formulated with one objective. multi-objective CGO proposed in study is utilized to handle the several objectives (MOCGO). In MOCGO, Pareto-optimal...

Journal: :international journal of smart electrical engineering 0
naser ghorbani eastern azarbayjan electric power distribution company, faculty of electrical and computer engineering, university of tabriz ebrahim babaei faculty of electrical and computer engineering, university of tabriz, sara laali faculty of electrical and computer engineering, university of tabriz payam farhadi young researchers club, parsabad moghan branch, islamic azad university

this paper proposes per unit coding for combined economic emission load dispatch problem. in the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. in the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. in this paper, particle sw...

Journal: :iranian journal of chemistry and chemical engineering (ijcce) 2007
maryam sadi bahram dabir

a multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. for this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing experim...

Journal: :Discrete Applied Mathematics 2013

Journal: :Aeronautics and Aerospace Open Access Journal 2019

Journal: :Int. J. Comput. Syst. Signal 2005
Martin Brown Robert E. Smith

While evolutionary computing inspired approaches to multi-objective optimization have many advantages over conventional approaches; they generally do not explicitly exploit directional/gradient information. This can be inefficient if the underlying objectives are reasonably smooth, and this may limit the application of such approaches to real-world problems. This paper develops a local framewor...

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