Improvements to Dual Annealing in SciPy

It has recently been shown that a typical implementation of Simulated Annealing in continuous domains is effectively the same as random search/Hill Climbing. This result is repeated for Dual Annealing that exists as a popular and highly used optimization method in SciPy. A simpler version of Hill Climbing is then developed, and a restart-based version with local search is able to achieve better overall results on the CEC2022 benchmark functions.