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View article: Dynamic Job Shop Scheduling Problem With New Job Arrivals Using Hybrid Genetic Algorithm
Dynamic Job Shop Scheduling Problem With New Job Arrivals Using Hybrid Genetic Algorithm Open
The present paper tackles the dynamic job shop scheduling problem (DJSSP), aiming to schedule a new set of jobs while minimizing the completion time of all operations. The problem is an NP-hard combinatorial optimization problem. This cont…
View article: Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression
Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression Open
Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly u…
View article: Discretization-Based Feature Selection as a Bilevel Optimization Problem
Discretization-Based Feature Selection as a Bilevel Optimization Problem Open
Discretization-based feature selection (DBFS) approaches have shown interesting results when using several metaheuristic algorithms, such as particle swarm optimization (PSO), genetic algorithm (GA), ant colony optimization (ACO), etc. How…
View article: Multi-Agent Cooperation for an Active Perception Based on Driving Behavior: Application in a Car-Following Behavior
Multi-Agent Cooperation for an Active Perception Based on Driving Behavior: Application in a Car-Following Behavior Open
Perception is presented as a predominant concern in the functioning of a driving system, where it is necessary to understand how the information, events, and actions of each influence the state of the environment and the objectives of the …
View article: Solving Combinatorial Multi-Objective Bi-Level Optimization Problems Using Multiple Populations and Migration Schemes
Solving Combinatorial Multi-Objective Bi-Level Optimization Problems Using Multiple Populations and Migration Schemes Open
Many decision making situations are characterized by a hierarchical structure where a lower-level (follower) optimization problem appears as a constraint of the upper-level (leader) one. Such kind of situations is usually modeled as a BLOP…
View article: Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior
Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior Open
International audience
View article: Anticipation model based on a modified fuzzy logic approach
Anticipation model based on a modified fuzzy logic approach Open
Car‐following behaviour is an important problem in terms of road safety, since it represents, alone, almost 70% of road accidents caused by not maintaining a safe braking distance between the moving cars. The inappropriate anticipation of …
View article: A Co-evolutionary Decomposition-based Chemical Reaction Algorithm for Bi-level Combinatorial Optimization Problems
A Co-evolutionary Decomposition-based Chemical Reaction Algorithm for Bi-level Combinatorial Optimization Problems Open
Bi-level optimization problems (BOPs) are a class of challenging problems with two levels of optimization tasks. The main goal is to optimize the upper level problem which has another optimization problem as a constraint. In these problems…
View article: Many-Objective Software Remodularization Using NSGA-III
Many-Objective Software Remodularization Using NSGA-III Open
Software systems nowadays are complex and difficult to maintain due to continuous changes and bad design choices. To handle the complexity of systems, software products are, in general, decomposed in terms of packages/modules containing cl…