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💡 Ten optimization algorithms: HTO, SA, Gradient, Adam, Tabu Search, VNS, GRASP, GA, Memetic, and Differential Evolution

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Optimization Algorithm

Network Parameters

Grid Size: 10×10
Min Drainage: 1
Energy Exp (γ): 1.0

Algorithm Parameters

Hill Tunneling (HTO): Makes k sequential swaps before evaluating. Learns successful k values over time. Phase 1 uses uniform random k, Phase 2 uses learned distribution.

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Network Metrics

Total Length: 0
Channel Count: 0
Bifurcation Ratio: 0.0
Total Energy: 0.0
Max Flow: 0

Algorithm Status

Mode: HTO
Status: Phase 1
Evaluations: 0
Improvements: 0
Accept Rate: 0%
Success Lengths: 0