The document discusses various methods for optimization in machine translation decoding, including loss minimization, minimum error rate training (MERT), softmax loss, max margin loss, pairwise ranking optimization, and minimum Bayes risk. It covers challenges like non-differentiable error functions and vast search spaces, and how different methods address these challenges through techniques like Powell's method, gradient-based methods, and sentence-level BLEU approximations.