For the proposal η(x t |x t-1 ), we employ a mixture model such that a neighboring reactant of each in x t-1 is selected from B t with probability α, and with probability 1 -α, x t is chosen completely at random from B t × B t in order to obtain a renewed x t . Probability α is a hyperparameter that controls the trade-off between "exploitation" and "exploration". The "exploration" creates a mechanism that enhances the diversity of solutions. The problem we face here is the computational cost of the neighborhood search. The set of candidate reactants B t grows monotonically with each step. Calculating the similarity between all entries in {x i t-1 |i = 1, . . . , m} and the monotonically increasing B t at every step is quite time-consuming. Therefore, we introduce a method to reduce the computational complexity, as described below.