Inverse theorem in dynamic programming III

Declarative Dynamic Programming as an Alternative Realization of Courcelle's Theorem

Many computationally hard problems become tractable if the graph structure underlying the problem instance exhibits small treewidth. A recent approach to put this idea into practice is based on a declarative interface to specify dynamic programming over tree decompositions, delegating the computation to dedicated solvers. In this paper, we prove that this method can be applied to any problem wh...

Theorem Proving and Programming with Dynamic First Order Logic

An Inverse Spectral Theorem

We prove a substantial extension of an inverse spectral theorem of Ambarzumyan, and show that it can be applied to arbitrary compact Riemannian manifolds, compact quantum graphs and finite combinatorial graphs, subject to the imposition of Neumann (or Kirchhoff) boundary conditions.

Inverse Linear Programming in DEA

Despite the large uses of inverse DEA models, there is not any single application of inverse linear programming in DEA when the definition of inverse linear programming is taken under account. Thus the goal of this paper is applying the inverse linear programming into DEA field, and to provide a streamlined approach to DEA and Additive model. Having the entire efficient DMUs in DEA models is a...

On Burr III-Inverse Weibull Distribution with COVID-19 Applications

We introduce a flexible lifetime distribution called Burr III-Inverse Weibull (BIII-IW). The new proposed distribution has well-known sub-models. The BIII-IW density function includes exponential, left-skewed, right-skewed and symmetrical shapes. The BIII-IW model’s failure rate can be monotone and non-monotone depending on the parameter values. To show the importance of the BIII-IW distributio...