Overall Objectives
Research Program
Application Domains
New Results
- Benchmarking Numerical Optimizers
- Handling numeric and temporal data in a local search-based classification algorithm
- MO-DYNAMOP
- Decomposition-based multi-objective optimization
- Fitness landscape analysis for multi-objective optimization
- Fitness Landscape of the Factoradic Representation on the PFSP
- How Neutrality Helps Multiobjective Local Search Algorithms
- Surrogate-assisted multiobjective evolutionary algorithm for fuzzy job shop problems
- Bipartite matching approximation
- Parallel B&B revisited for coprocessors using our new IVM data structure dedicated to permutation problems
- large scale heterogeneous parallel B&B based on hybrid work-stealing
- A Multi-objective Evolutionary Algorithm for Cloud Platform Reconfiguration
- A multi-objective approach for energy-efficient scheduling of large workloads in multicore distributed systems
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography
Overall Objectives
Research Program
Application Domains
New Results
- Benchmarking Numerical Optimizers
- Handling numeric and temporal data in a local search-based classification algorithm
- MO-DYNAMOP
- Decomposition-based multi-objective optimization
- Fitness landscape analysis for multi-objective optimization
- Fitness Landscape of the Factoradic Representation on the PFSP
- How Neutrality Helps Multiobjective Local Search Algorithms
- Surrogate-assisted multiobjective evolutionary algorithm for fuzzy job shop problems
- Bipartite matching approximation
- Parallel B&B revisited for coprocessors using our new IVM data structure dedicated to permutation problems
- large scale heterogeneous parallel B&B based on hybrid work-stealing
- A Multi-objective Evolutionary Algorithm for Cloud Platform Reconfiguration
- A multi-objective approach for energy-efficient scheduling of large workloads in multicore distributed systems
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography
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