Pages that link to "Item:Q2183854"
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The following pages link to A learning-based metaheuristic for a multi-objective agile inspection planning model under uncertainty (Q2183854):
Displaying 7 items.
- 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)
- A closed-loop supply chain model with learning effect, random return and imperfect inspection under price- and quality-dependent demand (Q2085511) (← links)
- Hazardous material transportation problems: a comprehensive overview of models and solution approaches (Q2140311) (← links)
- Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: a state-of-the-art (Q2242290) (← links)
- Hybrid neuro-fuzzy approach to the generation of measuring points for knowledge-based inspection planning (Q4807205) (← links)
- Agile two-stage lot-sizing and scheduling problem with reliability, customer satisfaction and behaviour under uncertainty: a hybrid metaheuristic algorithm (Q5059407) (← links)
- Multi-objective energy-efficient hybrid flow shop scheduling using Q-learning and GVNS driven NSGA-II (Q6047920) (← links)
