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An optimization approach and a heuristic procedure to schedule battery charging processes for stackers of palletized cargo
(2019)
This paper proposes an approach to develop schedules for charging batteries in a battery center. This problem arises in warehouses and logistics centers that attempt to provide uninterrupted operations with battery powered ...
Exploring data-driven selection hyper-heuristic approaches for the curriculum-based course timetabling
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-12)
The curriculum-based timetabling problem (CB-CTT) represents a challenging field of study within educational timetabling, with real-world applications that stress its importance. Solving a CB-CTT problem requires allocating ...
Modelo hiper-heurístico baseado em redes de autômatos estocásticos com aprendizado
(Universidade do Vale do Rio dos Sinos, 2020-04-28)
In the last decade, there has been a substantial increase in works about metaheuristics based on metaphors. Although these works have produced effective solutions within their proposals, the scientific community criticizes ...
Modelo hiper-heurístico baseado em redes de autômatos estocásticos com aprendizado
(Universidade do Vale do Rio dos Sinos, 2020-04-28)
In the last decade, there has been a substantial increase in works about metaheuristics based on metaphors. Although these works have produced effective solutions within their proposals, the scientific community criticizes ...
An iterated greedy algorithm for total flow time minimization in unrelated parallel batch machines with unequal job release times
(Engineering Applications of Artificial Intelligence, 2019)
Oxygen integration between a gasification process and oxygen production using a mass exchange heuristic
(Elsevier, 2016-01)
In this work we analyze different design alternatives for the integration of a gasification process with the oxygen production process, through ITM membranes. We analyze the conventional separation design compared with a ...
On the Use of Meta-Heuristic Algorithms for Automated Test Suite Generation in Software Testing
There exists a dire need to automate the process of test suite generation to get the most optimal results as testing accounts for more than 40% of total cost. A solution consists of using meta-heuristic algorithms which ...
Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization
(2020-07-01)
Restricted Boltzmann Machines (RBM) are stochastic neural networks mainly used for image reconstruction and unsupervised feature learning. An enhanced version, the temperature-based RBM (T-RBM), considers a new temperature ...
Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization
(Ieee, 2020-01-01)
Restricted Boltzmann Machines (RBM) are stochastic neural networks mainly used for image reconstruction and unsupervised feature learning. An enhanced version, the temperature-based RBM (T-RBM), considers a new temperature ...