Multiobjective Evolutionary Optimization
Multiobjective evolutionary optimization of water distribution systems : exploiting diversity with infeasible solutions
... in multiobjective evolutionary optimization algorithms for water distribution systems based on the coexistence and simultaneous development of subpopulations of cost-effective feasible and infeasible ...
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Overview of Multiobjective Optimization Methods in in Silico Metabolic Engineering
... objective optimization, multiobjective optimization involves optimizing multiple conflicting ...Abstract: Multiobjective optimization requires of finding a trade-off between multiple ...
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Defects Detection of TFT Lines of Flat Panel Displays Using an Evolutionary Optimized Recurrent Neural Network
... Therefore, in this paper, as an attractive alternative, we propose a recurrent neural network (RNN) based de- fect inspection method to address and overcome the above mentioned drawbacks in our previous method that was ...
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MOEA/D-GO for Fragmented Antenna Design
... hybrid multiobjective evolutionary algorithm, MOEA/D-GO (Multiobjective Evolutionary Algorithm Based on Decomposition combined with Enhanced Genetic Operators), is proposed for fragment-type ...
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Parametric design and multiobjective optimization of containerships
... design optimization in the shipbuilding industry are ...metric optimization process in the early stages of ship design, a much improved design can be produced, providing numerous benefits to a potential ...
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On the Sensitivity of Aggregative Multiobjective Optimization Methods
... Not all these transformation methods ( also called aggregation methods ) are equivalent. Some of these transformations are sufficiently “efficient” so as to deal with a non convex multiobjective ...
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Reactive Search Optimization; Application to Multiobjective Optimization Problems
... an optimization algorithm is applied in order to optimize the function to improve the quality of the ...brain-computer evolutionary multiobjective optimization implementations and ...
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Hybrid Swarm Algorithm for Multiobjective Optimal Power Flow Problem
... the multiobjective optimal power flow problem using a new hybrid technique by combining the particle swarm optimization and ant colony ...and multiobjective func- ...
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Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection
... to evolutionary multiobjective feature selection are proposed with different structures of ...proposed evolutionary multiobjective feature selection approaches provide similar or even better ...
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UTILITARIAN MECHANISM DESIGN FOR MULTIOBJECTIVE OPTIMIZATION
... idea is to round costs, lengths, and target values so that they range in a polynomial-size set. The rounding is such that the gap problem in the original instance is equivalent to a feasibility problem in the rounded ...
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Limit Cycle Prediction Based on Evolutionary Multiobjective Formulation
... a multiobjective problem. The multiobjective genetic algorithm is employed to obtain quantitative values for parameters of possible limit cycle ...a multiobjective problem and subsequent solution by ...
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Generating Epsilon Efficient Solutions in Multiobjective Optimization by Genetic Algorithm
... multi-objective optimization problems ...objective optimization problem, one has to consider a finite discretization of the set of feasible points (see Section 3 ...
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Solving Multi-objective Fuzzy Matrix Games via Fuzzy Relation Approach
... non-linear optimization problems, and then the pair of multi- objective non-linear optimization problems can be reduced to two mutually dual multi-objective linear programming prob- ...
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A novel multiobjective evolutionary algorithm based on regression analysis
... continuous multiobjective optimization problem with 𝑚 objective functions is a piecewise continuous (𝑚 − 1)-dimensional manifold in the decision space under some mild ...design multiobjective ...
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Economic Operation of Self Sustained Microgrid Optimal Operation by Multiobjective Evolutionary Algorithm Based on Decomposition
... Total operation cost of the proposed method has been compared with the well-known algorithms such as particle swarm optimization (PSO) and genetic algorithm (GA) methods. The results are reported in Table II, that ...
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Optimality and Duality Theorems in Nonsmooth Multiobjective Optimization
... Auslender [6] obtained necessary and sufficient conditions for a strict local minimi- zer of first and second order, supposing that the objective function f is locally Lipschit- zian and that the feasible set S is ...
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Output sensitive complexity of multiobjective combinatorial optimization
... picture: Multiobjective versions of even the simplest combinatorial optimization problems have Pareto-fronts of exponential size, and thus there is no prospect for finding polynomial time algorithms to ...
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Differential Evolution based Multiobjective Optimization A Review
... The earliest way to solve MOP problems are by using Penalty function method or weighing factor method. The former method is applied to solve biobjective problem [1]. Here consider one objective as constraint and thus ...
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Solution Concepts and New Optimality Conditions in Bilevel Multiobjective Programming
... bilevel multiobjective optimization, in the general case were both the higher and the lower level problems are ...level) multiobjective optimization problems (MOP), we established new ...
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MULTIOBJECTIVE LINEAR PROGRAMMING MODEL WITH WEIGHTED INTERVALS IN A MINIMUM CONSENSUS SCENARIO FOR PRODUCTION PLANNING
... presentsa multiobjective linear programming (MOLP) model in which the cost coefficients of each decision variable of the objective functions aremodeledin weighted intervals and there exists a minimum consensus ...
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