Pages that link to "Item:Q5925164"
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The following pages link to Combining metaheuristics with mathematical programming, constraint programming and machine learning (Q5925164):
Displaying 16 items.
- Hybridizing exact methods and metaheuristics: a taxonomy (Q1042187) (← links)
- A matheuristic approach for the quickest multicommodity \(k\)-splittable flow problem (Q1651593) (← links)
- Accelerating the branch-and-price algorithm using machine learning (Q1653391) (← links)
- On the use of learnheuristics in vehicle routing optimization problems with dynamic inputs (Q1712070) (← links)
- Learning to select operators in meta-heuristics: an integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem (Q2079447) (← links)
- Constraint programming and local search heuristic: a matheuristic approach for routing and scheduling feeder vessels in multi-terminal ports (Q2226489) (← links)
- A novel solution approach with ML-based pseudo-cuts for the flight and maintenance planning problem (Q2241911) (← links)
- Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: a state-of-the-art (Q2242290) (← links)
- Modeling with metaconstraints and semantic typing of variables (Q2806860) (← links)
- Hybrids of Constructive Metaheuristics and Constraint Programming: A Case Study with ACO (Q2950522) (← links)
- Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain (Q3411293) (← links)
- Matheuristics (Q3654149) (← links)
- Combining metaheuristics with mathematical programming, constraint programming and machine learning (Q5891242) (← links)
- Pattern mining‐based pruning strategies in stochastic local searches for scheduling problems (Q6082181) (← links)
- Parallel matheuristics for the discrete unit commitment problem with min‐stop ramping constraints (Q6088241) (← links)
- Research trends in combinatorial optimization (Q6091419) (← links)
