نتایج جستجو برای: moeas have been used for solving multi
تعداد نتایج: 11409127 فیلتر نتایج به سال:
Multiobjective optimization problems (MOPs) have attracted intensive efforts from AI community and many multiobjective evolutionary algorithms (MOEAs) were proposed to tackle MOPs. In addition, a few researchers exploited MOEAs to solve constraint optimization problems (COPs). In this paper, we investigate how to tackle a MOP by iteratively solving a series of COPs and propose the algorithm nam...
In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered: (i) the complexity of the search space and (ii) the non-monotonicity of the objective-space. Here, we introduce a hierarchical problem description (chromosomes) to deal with the complexity of the search space. Since Evolutiona...
The paper is a short survey of recent developments in the area of word maps evaluated on groups and algebras. It is aimed to pose questions relevant to Kac–Moody theory.
A mathematical model and heuristic method for solving multi-depot and multi-product vehicle routing problem with heterogeneous vehicle have been proposed in this paper. Customers can order several products and depots must deliver customer's orders before due date with different vehicle. Hence mathematical model of multi-depot vehicle routing problem has been developed to represent these condi...
all analytical methods are generally based on the measurement of a parameter or parameters which are somehow related to the concentration of the species.an ideal analytical method is one in which the concentration of a species can be measured to a high degree precision and accuracy and with a high sensitivity. unfortunately finding such a method is very difficult or sometimes even impossible.in...
Multi-objective evolutionary algorithms (MOEAs) have been successfully applied for the numerical treatment of multi-objective optimization problems (MOP) during last three decades. One important task within MOEAs is archiving (or selection) computed candidate solutions, since one can expect that an MOP has infinitely many solutions. We present and analyze in this work ArchiveUpdateHD, which a b...
The multi-objective optimization problem is difficult to solve with conventional methods and algorithms because there are conflicts among several objectives functions. Through the efforts of researchers experts from different fields for last 30 years, research application evolutionary (MOEA) have made excellent progress in solving such problems. MOEA has become one primary used technologies rea...
in this thesis, a structured hierarchical methodology based on petri nets is used to introduce a task model for a soccer goalkeeper robot. in real or robot soccer, goalkeeper is an important element which has a key role and challenging features in the game. goalkeeper aims at defending goal from scoring goals by opponent team, actually to prevent the goal from the opponent player’s attacks. thi...
this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...
Water distribution network design is a complex multi-objective optimization problem and evolutionary algorithms (MOEAs) such as NSGA II have been widely used to solve this problem. However, networks get larger, struggles find the diverse uniform solutions that are critical in optimization. This research proposes an improved version of uses three new-generation methods target different regions P...
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