Pages that link to "Item:Q2814293"
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The following pages link to A statistical learning based approach for parameter fine-tuning of metaheuristics (Q2814293):
Displaying 11 items.
- Problem dependent optimization (PDO) (Q266075) (← links)
- Improving the performance of metaheuristics: an approach combining response surface methodology and racing algorithms (Q277580) (← links)
- AEGIS---attribute experimentation guiding improvement searches (Q1038838) (← links)
- On metaheuristics for solving the parameter estimation problem in dynamic systems: a comparative study (Q1659343) (← links)
- Methods for improving the efficiency of swarm optimization algorithms. A survey (Q1982839) (← links)
- Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem (Q2030552) (← links)
- New variable-length data compression scheme for solution representation of meta-heuristics (Q2668691) (← links)
- Horizontal collaboration in freight transport: concepts, benefits and environmental challenges (Q4606123) (← links)
- Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities (Q4969270) (← links)
- A simheuristic algorithm for time-dependent waste collection management with stochastic travel times (Q5158698) (← links)
- On the role of metaheuristic optimization in bioinformatics (Q6056877) (← links)