This research sheds light on the use of metal in the manufacture of jewelry, which is represented by ornamental tools in the period between the third and second millennium BC, in addition to the most important molds used in their manufacture. Man has been interested in metals since early ages, and was able to make tools that he uses in his daily life, especially jewelry. And the Syrian people got acquainted with the types of minerals, their characteristics, and how to deal with them. Minerals played an effective and prominent role in the economy of ancient Syria. Trade with those countries and secure their roads.

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

An idiom is a group of words whose meaning put together is different from the meaning of
individual words. English is a rich language when it comes to idioms, they represent variety. For
foreign learners, idioms are problematic because even if they know the meaning of individual
words that compose an idiom the meaning of it might be something completely different.
The present study investigates Iraqi third year college students’ recognition of idioms. To
achieve this, the researchers have conducted a test which comprises three questions. Certain
conclusions are reached here along with some suggestions and recommendations.

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).