Optimality-based clustering: An inverse optimization approach

We propose a new clustering approach, called optimality-based clustering, that clusters data points based on their latent decision-making preferences. assume each point is decision generated by decision-maker who (approximately) solves an optimization problem and cluster the identifying common objective function of problems for such worst-case optimality error minimized. three different models test them in diet recommendation application.