Pages that link to "Item:Q2333140"
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The following pages link to Deep learning assisted heuristic tree search for the container pre-marshalling problem (Q2333140):
Displaying 23 items.
- Machine learning meets mathematical optimization to predict the optimal production of offshore wind parks (Q1734857) (← links)
- Machine learning for combinatorial optimization: a methodological tour d'horizon (Q2029358) (← links)
- Neural large neighborhood search for routing problems (Q2093389) (← links)
- Deep policy dynamic programming for vehicle routing problems (Q2170197) (← links)
- Robust optimization for premarshalling with uncertain priority classes (Q2189929) (← links)
- A feature-extraction-based lightweight convolutional and recurrent neural networks adaptive computing model for container terminal liner handling volume forecasting (Q2232683) (← links)
- A branch and bound approach for large pre-marshalling problems (Q2424778) (← links)
- Pre-processing a container yard under limited available time (Q2664376) (← links)
- A weighted-sum method for solving the bi-objective traveling thief problem (Q2669668) (← links)
- A beam search algorithm for minimizing crane times in premarshalling problems (Q2672129) (← links)
- Optimizing the number of deployed yard cranes in a container terminal (Q5883816) (← links)
- An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents (Q6087487) (← links)
- A constraint programming approach for the premarshalling problem (Q6106491) (← links)
- Machine learning augmented approaches for hub location problems (Q6109558) (← links)
- Novel models and algorithms for location assignment for outbound containers in container terminals (Q6112558) (← links)
- The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions (Q6113444) (← links)
- Integer programming model and branch-and-cut algorithm for the stack inbound and pre-marshalling problem (Q6164614) (← links)
- A tree search algorithm for uncertainty-considered consecutive discharging and loading operations between ship and offshore platform (Q6554672) (← links)
- Learning to sample initial solution for solving 0-1 discrete optimization problem by local search (Q6564766) (← links)
- The container premarshalling problem under limited crane time: a constraint programming approach (Q6568426) (← links)
- One-shot learning for MIPs with SOS1 constraints (Q6579097) (← links)
- A deep reinforcement learning assisted simulated annealing algorithm for a maintenance planning problem (Q6589065) (← links)
- Global optimization: a machine learning approach (Q6667701) (← links)
