Today, models of cooperative games with transferable utility (TU-games for short) have been widely used in many fields including economics. One of the most important problems in cooperative TU-games is to determine rational imputation, and computing such imputation within a limited time is of practical importance. So far, cooperative TU-games have used the Shapley value and the nucleolus to determine imputation, but the problem of computing the nucleolus of classical TU-games is NP-hard. In addition, the Shapley value computation in classical cooperative TU-games requires exponential time.
GWO (Grey Wolf Optimizer) is an algorithm to solve optimization problems by simulating the foraging process of grey wolves.
O Un Suk, a lecturer at the Faculty of Applied Mathematics, proposed an algorithm for computing rational imputation (an element of the core) in TU-games with nonempty core within a limited time.
The calculation experimental results demonstrated that the proposed algorithm is much better than the calculation of the Shapley value if the number of players exceeds four in classical TU-games.
If more details are needed, please refer to her paper “Algorithm for Computing the Rational Imputation using Grey Wolf Optimizer in Cooperative TU-Games” in “Proceedings of KUTIC-2025”.