Multi-objective Genetic Algorithms
Modeling and Optimization of Precedence-Constrained Production Sequencing and Scheduling Using Multi-Objective Genetic Algorithms
... In this paper, a class of soft precedence-constrained production sequencing and scheduling problems has been modelled. To optimise the model for two objective functions at the same time, multi ...
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A new method for feature selection based on fuzzy similarity measures using multi objective genetic algorithm
... by multi objective genetic algorithm (FSFSM – MOGA) is introduced and performance of the proposed method on published data sets from UCI was ...method multi-objective genetic ...
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EVALUATION OF ASSEMBLY LINE BALANCING METHODS USING AN ANALYTICAL HIERARCHY PROCESS (AHP) AND TECHNIQUE FOR ORDER PREFERENCES BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) BASED APPROACH
... the multi-objective worker allocation problems of single and mixed- model assembly lines having manually operated machines in several fixed U-shaped ...Three objective functions are simultaneously ...
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Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations
... known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg ...a multi-objective ...apply multi-objective algorithms to an ...
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Determination of Turbulence Coefficient using Genetic Algorithms
... For the past few years GA has been widely used by hydrologists and hydro-geologists for solution of groundwater and solute transport problems. Memon, et. al. [21] used GA as an optimization tool for identification of ...
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A Multi-objective Approach for Multi-commodity Location within Distribution Network Design Problem
... a multi-objective genetic algorithm (MOGA) to find a set of optimal pareto solution for Supply chain network (SCN) ...heuristic algorithms for considering concept of safety stock in supply ...
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Multi-objective metaheuristic algorithms for the resource-constrained project scheduling problem with precedence relations
... Several multi-objective optimization methods can be found in literature to solve this class of ...the objective function vector into a scalar objective function, as it is the case of the ...
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Multi-objective approaches for the open-pit mining operational planning problem
... heuristic algorithms. Unlike [9], who treated the problem through a mono-objective optimization algorithm, we develop here three multi-objective heuristic ...on Multi-objective ...
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JISTEM J.Inf.Syst. Technol. Manag. vol.12 número3
... search algorithms for effective cost ...based genetic algorithm model to solve the multi-objective passenger railway scheduling problem aiming to optimize total operational costs at a ...
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GENETIC ALGORITHMS APPLIED TO ASSET LIABILITY MANAGEMENT
... of genetic algorithms can be found in Finance, particularly in the sub-field of portfolio ...variance. Genetic algorithms are very well suited to perform portfolio optimization because the ...
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Hybrid Genetic Algorithms: A Review
... pure genetic algorithm and their effectiveness deteriorates with an increasing use of learning in contrast to Lamarckian ...the multi-objective 0/1 knapsack problem using a single population model, ...
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Non-dominated Sorting Genetic Algorithms for Heterogeneous Embedded System Design
... The multi-objective evolutionary algorithms (EA) are the best choice because of its population-based ...as genetic operators (such as recombination and ...
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Multi-objective Numeric Association Rules Mining via Ant Colony Optimization for Continuous Domains without Specifying Minimum Support and Minimum Confidence
... the algorithms RPSOA [13], the Genetic Association Rule Mining algorithm [24] and SA [25] find directly numeric association rules without finding frequent itemsets and search for numeric intervals while ...
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Abstract — The physical topology design (PTD) of optical
... Sorting Genetic Algorithm II ...combinatorial multi-objective optimization problems, especially if two conflicting objectives are considered ...SPEA2 algorithms provide the best ...the ...
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Approach Multiclass SVM Utilizing Genetic Algorithms
... The optimal tree (best individual) created by genetic algorithms is implemented to obtain a multiclass approach. Takes advantage of both the efficient computation of the tree architecture and the high ...
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Structural Topology Optimization Using Genetic Algorithms
... Genetic algorithm was first introduced by Holland in 1975 [4]. It simulates the natural evolutionary process to generate better or fittest species to survive the environment. Three artificial evolutionary ...
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A comparison of energy consumption prediction models based on neural networks of a bioclimatic building
... The objective of this paper is to compare a neural network based model obtained in [17] with the models obtained by a multi objective genetic algorithm (MOGA), to predict the electric power ...
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Fo rce ( k N )
... In this study crashworthiness optimization of nested and concentric circular tubes under impact loading is performed by coupling Finite Element model, Response Surface Models and Genetic Algorithm. Specific Energy ...
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Genetic algorithms for the traveling salesman problem
... Gucht, The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem, in: Proc. Johnson, Local[r] ...
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Genetic Algorithms for a Parameter Estimation of a Fermentation Process Model: A Comparison
... using genetic algorithms is performed. A comparison of three genetic algorithms, namely simple, modified and multi-population genetic algorithms is ...the genetic ...
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