ARMGAAM: Multi-Objective Evolutionary Algorithm Using Adaptive
DECMO2: a robust hybrid and adaptive multi-objective evolutionary algorithm.
... and adaptive coevolu- tionary optimization method that can efficiently solve a wide range of multi-objective optimization problems (MOOPs) as it successfully combines positive traits from three main ...
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Impact analysis of crossovers in a multi-objective evolutionary algorithm
... the evolutionary process of population baaed evolutionary ...in multi-objective optimization ...chosen multi-objective evolutionary algorithm based on decomposition ...
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Portfolio optimization with an envelope-based multi-objective evolutionary algorithm
... our algorithm, we introduced two additional concepts: duplicate elimination and a variable population ...an adaptive population size, namely to work with an equally large population as the point-based ...
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Software Module Clustering using a Fast Multi-objective Hyper-heuristic Evolutionary Algorithm
... Fast Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution of Multi- objective software module ...the multi-objective software module ...
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A multi tier adaptive grid algorithm for the evolutionary multi objective optimisation of complex problems
... novel multi-tier adaptive grid selection scheme is developed and combined with the existing CMA-PAES algorithm, in a new augmented algorithm named the Multi-tier Covariance Matrix ...
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A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems
... novel multi-tier adaptive grid selection scheme is developed and combined with the existing CMA-PAES algorithm, in a new augmented al- gorithm named the Multi-tier Covariance Matrix Adap- ...
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Multi-drop Container Loading using a Multi-objective Evolutionary Algorithm
... Keywords: evolutionary algorithms, multi-objective optimisation, cutting & packing. I. I NTRODUCTION The single container loading problem is a three-dimensional optimisation problem from the ...
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A parallel implementation of a multi-objective evolutionary algorithm
... several diverse solutions that can serve as leads is generally preferred. Based on this requirement a truly multiobjective de novo design system must be able to produce multiple, diverse solutions and enable users to ...
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Self-Adaptive Mechanism for Multi-objective Evolutionary Algorithms
... 2. Deb et al.’s approach is limited by the requirement of a priori knowledge of the target solutions distribution. Using this information, the number of grids can be determined/fitted. Nevertheless in real ...
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Risk-adjusted portfolio optimisation using a parallel multi-objective evolutionary algorithm
... measures. Multi-objective optimisation algorithms attempt to solve problems that have multiple overlapping or possibly competing objectives ...particular, multi-objective algorithms have been ...
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Multi-objective optimization of vehicle routing problem using evolutionary algorithm with memory
... new evolutionary algorithm with a memory aspect included is proposed to find a multi-objective optimized solution for the vehicle routing problem with time ...This algorithm uses a ...
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A New Multi-objective Evolutionary Optimisation Algorithm: The Two-Archive Algorithm
... Two-Archive algorithm using the example, the convergence archive consists of two members, solutions 1 and 2, and members in the diversity archive are solutions 3 and ...
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An adaptive evolutionary multi objective approach based on simulated annealing
... 7.1.4 Updating the External Population with -dominance In MOEA/D, no diversity strategy is applied to manage the external population. This is not a problem when the size of the POF is small. However, for large fronts, ...
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An adaptive evolutionary multi-objective approach based on simulated annealing
... A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic ...an evolutionary ...
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A novel multi-objective evolutionary algorithm based on space partitioning
... The three decomposition methods of MOEA/D are sensitive to the shapes of PF, and it is difficult to solve the PF with the shape of nonconvex or ex- tremely convex. For Penalty-based Boundary Intersection (PBI), it is ...
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Computational steering of a multi objective evolutionary algorithm for engineering design
... The implementation of this steering client can be effec- tively realised by using a PDA enabled with a wireless con- nection. The low cost involved in the use of a PDA-based client would allow a wide uptake of ...
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Convex hull ranking algorithm for multi-objective evolutionary algorithms
... of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent ...most multi-objective ...
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A Pareto-based evolutionary algorithm using decomposition and truncation for dynamic multi-objective optimization
... the objective space has been widely recognized as the main challenge when solving problems with two or more conflicting ...Pareto-based evolutionary algorithm using decomposition and ...
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DNA Sequence Motif Discovery Using Evolutionary Multi Objective Differential Evolution Algorithm
... So, there can be infinite number of candidate motif locations and searching them computationally are both impractical as it requires exponential runtime. To solve this problem, many computational methods employing ...
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Aero-structural optimisation of unmanned aerial vehicles using a multi-objective evolutionary algorithm
... Parallel Evolutionary Algorithms for Multi-objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using high fidelity analysis ...designed Evolutionary Optimiser ...
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