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Hybrid Evolutionary Algorithm with Adaptive Crossover, Mutation and Simulated Annealing Processes to Project Scheduling
(Springer, 2015-09)
In this paper, we address a project scheduling problem that considers a priority optimization objective for project managers. This objective involves assigning the most effective set of human resources to each project ...
Scheduling Projects by a Hybrid Evolutionary Algorithm with Self-Adaptive Processes
(Springer, 2015-11)
In this paper, we present a hybrid evolutionary algorithm with self-adaptive processes to solve a known project scheduling problem. This problem takes into consideration an optimization objective priority for project ...
Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
(Elsevier B.V. Sa, 2012-08-01)
This paper proposes a multi-objective approach to a distribution network planning process that deals with the challenges derived from the integration of Distributed Generation (DG). The proposal consists of a multi-objective ...
Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
(Elsevier B.V. Sa, 2012-08-01)
This paper proposes a multi-objective approach to a distribution network planning process that deals with the challenges derived from the integration of Distributed Generation (DG). The proposal consists of a multi-objective ...
Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation
(ElsevierNew York, 2014-02-10)
Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting ...
Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem
(Institute of Electrical and Electronics Engineers (IEEE), 2010-06-01)
This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, ...
FP-AK-QIEA-R for Multi-Objective optimization
(Association for Computing Machinery, 2016)
The Evolutionary Algorithms have main features like: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The ...
Comparison of Multiobjective Evolutionary Algorithms for operations scheduling under machine availability constraints
(Hindawi Publishing Corporation, 2013-12)
Many of the problems that arise in production systems can be handled with Multi-Objective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer ...