Abstract: We would like to invite to a short presentation about the progress of a PostDoc research, which is belong to Optimal Search Problem.
There are several classical algorithms in that area, such as simplex method, ellipsoid method, interior point method etc. All of them have their own advantages and disadvantages. At the same time, they have one thing in common, namely, to start the search they require an initial feasible point. There is no special recommendations on how to find this point, and usually, these methods yhemselves are used to find the point. In other words, first, an optimum method is used to find an initial feasible point, and then optimum method searches for optimal value.
We want to demonstrate a method which works in reverse order, namely, it searches a feasible point and also can find an optimum solution. The method is based on geometrical properties of n-dimensional space and can be used on any type of linear constrains (>, =, ≥). Moreover it can be used when the feasible region is non-full-dimensional.
