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The optimization of the edge weights in optimal assignment methods is a valuable approach for ligand‐based virtual screening experiments.
Thus, the weights in the optimal assignment step in the 4DFAP can be optimized with our approach.
The optimal assignment problem is one of the basic discrete optimization problems.
In principle, the optimization of edge weights can be applied to any optimal assignment approach.
We also solve the optimal assignment problem of agents over subspaces.
Propositions for optimal assignment are presented where supplies cannot be split.
In this paper, we have adopted a game-theoretic approach to consider the optimal assignment of targets to vehicles.
The optimal assignment is formulated as an integer linear programming problem and is further converted into an equivalent graph problem.
The proposed algorithm finds the globally optimal assignment of orientations that simultaneously respects all common lines between all images.
We also find that the inefficiency of the optimal assignment rule decreases as the variability of the value distribution increases.
We characterize the structure of optimal assignment rules when both allocative inefficiency and expenditure inefficiency (e.g., rent-seeking) are present.
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