A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over Graphs
Recent years have witnessed a growing trend toward employing deep reinforcement
learning (Deep-RL) to derive heuristics for combinatorial optimization (CO) problems on …
learning (Deep-RL) to derive heuristics for combinatorial optimization (CO) problems on …
Hybrid Evolutionary Algorithm for the Overlap Constrained Resource Allocation Problem in Wireless Networks
Y Wang, Y Li, Z Wei, J Li - International Conference on Advanced …, 2024 - Springer
In wireless networks, efficiently allocating limited network resources holds significant
practical importance. This work focuses on the NP-hard overlap constrained resource …
practical importance. This work focuses on the NP-hard overlap constrained resource …
Efficient and Effective Local Search for the Set-Union Knapsack Problem and Budgeted Maximum Coverage Problem
W Zhu, L Luo - arXiv preprint arXiv:2207.00749, 2022 - arxiv.org
The Set-Union Knapsack Problem (SUKP) and Budgeted Maximum Coverage Problem
(BMCP) are two closely related variant problems of the popular knapsack problem. Given a …
(BMCP) are two closely related variant problems of the popular knapsack problem. Given a …
A Tabu Search Algorithm Based on Population Search Framework for Solving Multi-Budget Maximum Coverage Problem
Y Liu, D Pan - Available at SSRN 4457234 - papers.ssrn.com
The multi-budget maximum coverage problem (MMCP) is a natural and practical expansion
of both the budget maximum coverage problem (BMCP) and multiple knapsack problem …
of both the budget maximum coverage problem (BMCP) and multiple knapsack problem …