We demonstrate the algorithm's effectiveness

When such outliers occur at the end of the data stream, this can cause the final solution to have unexpectedly low accuracy.

The Job Shop Scheduling (JSS) problem can be viewed as an integer optimization program with linear objective function and linear, disjunctive constraints. Theconstraints(14c)enforceprecedencebetween tasks that must be scheduled in the specified order within their respective job. Themodel presented belowisusedtoconstruct solutions that are integral, and feasible tothe original problem constraints. However, the resolution frequency to solve OPFs is limited by their computational complexity. Additionally,the stochasticity introduced by renewable energy sources further increases the number of scenarios to consider. C.2 DatasetDetails Table 4 describes the power network benchmarks used, including the number of buses|N|, and transmission lines/transformers |E|.

Our initial investigation identifies which distributions accurately characterize the feature space, subsequently leveraging this priori to guide the alignment of the weakly supervised embeddings. Specifically, we analyze the superiority of the mixture of von Mises-Fisher distributions (moVMF) among several common distribution candidates.