Empirical comparison of four MOEAs on bi-objective stochastic MKP with chance constraints and dynamic capacities shows differences in behavior across uncertainty levels and change frequencies.
A deep reinforcement learning-based scheme for solving multiple knapsack problems.Applied Sciences, 12(6):3068
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On the Use of Bi-Objective Evolutionary Algorithms for the Stochastic MKP under Dynamic Constraints
Empirical comparison of four MOEAs on bi-objective stochastic MKP with chance constraints and dynamic capacities shows differences in behavior across uncertainty levels and change frequencies.