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Hybridizing a multi-objective simulated annealing algorithm with a multi-objective evolutionary algorithm to solve a multi-objective project scheduling problem
(Elsevier, 2012-11)
In this paper, a multi-objective project scheduling problem is addressed. This problem considers two conflicting, priority optimization objectives for project managers. One of these objectives is to minimize the project ...
A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
(Springer, 2014-09)
In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each ...
A hybrid evolutionary algorithm based on adaptive mutation and crossover for collaborative learning team formation in higher education
(Springer, 2017-10)
In this paper, we address a collaborative learning team formation problem in higher education environments. This problem considers a grouping criterion successfully evaluated in a wide variety of higher education courses ...
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 ...
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 ...
Hybrid algorithms for solving Sudokus [Algoritmos híbridos para la resolución de Sudokus]
(Institute of Electrical and Electronics Engineers Inc., 2015)
A hybrid algorithm for supply chain optimization of assembly companies
(IEEE, 2019)
A fundamental goal of any system is to get an optimal state. These optimal states can be found in different areas, such as medicine, engineering, or architecture. In the field of industrial engineering, one of its objectives ...
Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm
(2009-11-09)
This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The ...
Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm
(2009-11-09)
This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The ...
Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
(2013-08-21)
The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and ...