Efficiency aggregation and efficiency decomposition are two techniques used in modeling decision making units (DMUs) with two-stage network structures under network data envelopment analysis (DEA). Multiplicative efficiency decomposition (MED) is usually used in a very specialized two-stage structure when constant returns to scale (CRS) is assumed. MED-based network DEA retains the property of ...

Logic programming languages based on fragments of intuitionistic logic have recently been developed and studied by several researchers. In such languages, implications are permitted in goals and in the bodies of clauses. Attempting to prove a goal of the form D ⊃ G in a context τ leads to an attempt to prove the goal G in the extended context τ ∪{D}. While an intuitionistic notion of context ha...

A design point is inessential when it does not contribute to an optimal design, and can therefore be safely discarded from the space. We derive three inequalities for detection of such points in c-optimal design: first two are direct consequences equivalence theorem c-optimality; third one derived a second-order cone programming formulation design. Elimination rules A-optimal obtained as byprod...

Recently developed methods of monotonic optimization have been applied successfully for studying a wide class of nonconvex optimization problems, that includes, among others, generalized polynomial programming, generalized multiplicative and fractional programming, discrete programming, optimization over the efficient set, complementarity problems, etc. In the present paper the monotonic approa...

‎Bucket recursive trees are an interesting and natural‎ ‎generalization of ordinary recursive trees and have a connection‎ to mathematical chemistry‎. ‎In this paper‎, ‎we give the lower and upper bounds for the moment generating‎ ‎function and moments of the multiplicative Zagreb indices in a‎ ‎randomly chosen bucket recursive tree of size $n$ with maximal bucket size $bgeq1$‎. Also, ‎we consi...

A strategy that calculates an explicit state feedback policy to regulate constrained uncertain discrete-time linear systems is presented. We consider processes, affected by box-bounded multiplicative uncertainty as well bounded additive with and inputs constraints. The proposed method includes (i) the calculation of a terminal set constraint (ii) robust reformulation constraints in prediction h...

This paper presents an image space branch-reduction-bound algorithm for solving a class of multiplicative problems (MP). First all, by introducing auxiliary variables and taking the logarithm objective function, equivalent problem (EP) (MP) is obtained. Next, using new linear relaxation technique, parametric programming (PLRP) equivalence can be established acquiring lower bound optimal value t...

for fr$acute{mathbf{text{e}}}$chet algebras $(a, (p_n))$ and $(b, (q_n))$, a linear map $t:arightarrow b$ is textit{almost multiplicative} with respect to $(p_n)$ and $(q_n)$, if there exists $varepsilongeq 0$ such that $q_n(tab - ta tb)leq varepsilon p_n(a) p_n(b),$ for all $n in mathbb{n}$, $a, b in a$, and it is called textit{weakly almost multiplicative} with respect to $(p_n)$ and $(q_n)$,...

Algorithms based on convex optimization, especially linear and semidefinite programming, are ubiquitous in Computer Science. While there are polynomial time algorithms known to solve such problems, quite often the running time of these algorithms is very high. Designing simpler and more efficient algorithms is important for practical impact. In this thesis, we explore applications of the Multip...