in this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear bilevel programming (fflblp) problems by representing all the parameters as triangular fuzzy numbers. in the proposed method, the given fflblp problem is decomposed into three crisp linear programming (clp) problems with bounded variables constraints, the three clp problems are solved separately and...

in this paper, convex semi-infinite programming is converted to an optimal control model of neural networks and the optimal control model is solved by iterative dynamic programming method. in final, numerical examples are provided for illustration of the purposed method.

Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees aren’t uniform, the exact size of this tree isn’t known for most applications. Further, most games have transpositions, implying that there exists a minimal graph which is ...

The problem of verifiable data streaming (VDS) considers the setting in which a client outsources a large dataset to an untrusted server and the integrity of this dataset is publicly verifiable. A special property of VDS is that the client can append additional elements to the dataset without changing the public verification key. Furthermore, the client may also update elements in the dataset. ...

Simulating Hamiltonian dynamics is one of the most fundamental and significant tasks for characterizing quantum materials. Recently, a series algorithms employing block encoding Hamiltonians have succeeded in providing efficient simulation time-evolution operators on computers. While time-independent can be simulated by eigenvalue transformation (QET) or singular value with optimal query comple...

We initiate the rigorous study of classification in semimetric spaces, which are point sets with a distance function that is non-negative and symmetric, but need not satisfy the triangle inequality. We define the density dimension dens and discover that it plays a central role in the statistical and algorithmic feasibility of learning in semimetric spaces. We compute this quantity for several w...

A partial Steiner system Sp(t, k, n) is a collection of k-subsets (i.e. subsets of size k) of n element set such that every t-subset is contained in at most one k-subset. To avoid trivial cases, we assume 2 ≤ t < k < n. It is easy to see that the size of a partial Steiner system Sp(t, k, n) is at most ( n t )

In this paper, we consider the problem of Robust Matrix Completion (RMC) where the goal is to recover a low-rank matrix by observing a small number of its entries out of which a few can be arbitrarily corrupted. We propose a simple projected gradient descent-based method to estimate the low-rank matrix that alternately performs a projected gradient descent step and cleans up a few of the corrup...

majority of models in location literature are based on assumptions such as point demand, absence of competitors, as well as monopoly in location, products, and services. however in real-world applications, these assumptions are not well-matched with reality. in this study, a new mixed integer nonlinear programming model based on weighted goal programming approach is proposed to maximize the cap...