Finding and Exploring Promising Search Space for the 0-1 Multidimensional Knapsack Problem
Published in Applied Soft Computing, 164, 111934, 2024
The search space of the multidimensional knapsack problem is far too large to explore exhaustively, so the question is where to look. This work combines large neighbourhood search with evolutionary computation to identify promising regions, outperforming the state-of-the-art heuristics TPTEA and DQPSO as well as the commercial solver CPLEX, and establishing new lower bounds for ten large, hard instances.
Recommended citation: Jitao Xu, H. Li, M. Yin. (2024). "Finding and Exploring Promising Search Space for the 0-1 Multidimensional Knapsack Problem." Applied Soft Computing, 164, 111934.
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