  The algorithm and testing of the Multi-algorithm-collaborative Universal
Structure-prediction Environment ({\sc Muse}) are detailed. Presently, in {\sc
Muse} I combined the evolutionary, the simulated annealing, and the basin
hopping algorithms to realize high-efficiency structure predictions of
materials under certain conditions. {\sc Muse} is kept open and other
algorithms can be added in future. I introduced two new operators, slip and
twist, to increase the diversity of structures. In order to realize the
self-adaptive evolution of structures, I also introduced the competition scheme
among the ten variation operators, as is proved to further increase the
diversity of structures. The symmetry constraints in the first generation, the
multi-algorithm collaboration, the ten variation operators, and the
self-adaptive scheme are all key to enhancing the performance of {\sc Muse}. To
study the search ability of {\sc Muse}, I performed extensive tests on
different systems, including the metallic, covalent, and ionic systems. All
these present tests show {\sc Muse} has very high efficiency and 100% success
rate.
