Robust optimization algorithms for multi-objective knapsack problem
Takuya Miyamoto, Akihiro Fujiwara · 2022
The solution obtained using a simple optimization technique is affected by changes in variables in the real world due to errors and other factors, and thus the predicted optimality of the solution may not be guaranteed. Therefore, a robust optimal solution, which is less affected by changes in variables, has attracted considerable attention in recent years. In the present paper, we propose an optimization algorithm for robust solutions of the multi-objective knapsack problem. Experimental results show that our proposed algorithm obtains a wider range of solutions than the existing algorithm.