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Obtaining globally optimal solutions for optimization problems involve with DoCF is difficult and NP-hard [28].
Recently, many studies hybridize two or more algorithms to obtain optimal solutions for optimization problems [31].
The optimization formulations provide optimal solutions for resources allocation at, sometimes, the detriment of global convergence, computation time, and complexity.
The Pareto curve was obtained from the multiobjective optimization, allowing predicting the set of optimal solutions for the given problem.
We find the optimal solutions for these problems through formulating them as optimization models.
Table S4 Numbers of searched optimal solutions for C. chinensis.
We aim to find optimal solutions for Sokoban using PDBs.
Additionally, since the optimal solutions for existing test data is unknown, we propose a technique to generate test data with known optimal solutions for MCLCMP.
First of all, we show the existence of optimal solutions for ( P ε ).
Comparison between the optimal solutions for the two models is also given.
Open image in new window Fig. 11 Optimal solutions for instances 1, 5 and 10.
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