The classical methods for optimization are line search algorithms. Such an algorithm obtains a search direction in each iteration, and searches along this direction to obtain a better point. The search direction is a descent direction, normally computed by solving a subproblem that approximates the original optimization problem near the current iterate. Therefore, unless a stationary point is reached, there always exist better points along the search direction.
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Ya-xiang Yuan (2000) studied this question.