Relaxed verification for continuous problems

A Relaxed Extra Gradient Approximation Method of Two Inverse-Strongly Monotone Mappings for a General System of Variational Inequalities, Fixed Point and Equilibrium Problems

Can We Efficiently Check Concurrent Programs Under Relaxed Memory Models in Maude?

Relaxed memory models offer suitable abstractions of the actual optimizations offered by multi-core architectures and by compilers of concurrent programming languages. Using such abstractions for verification purposes is challenging in part due to their inherent non-determinism which contributes to the state space explosion. Several techniques have been proposed to mitigate those problems so to...

Discretization Methods for Semilinear Parabolic Optimal Control Problems

We consider an optimal control problem described by semilinear parabolic partial differential equations, with control and state constraints. Since this problem may have no classical solutions, it is also formulated in the relaxed form. The classical control problem is then discretized by using a finite element method in space and the implicit Crank-Nicolson midpoint scheme in time, while the co...

Existence results for equilibrium problems under strong sign property

This paper concerns equilibrium problems in real metric linear spaces. Considering a modified notion of  upper sign property for bifunctions, we obtain the relationship between the solution sets of the local Minty equilibrium problem and the equilibrium problem, where the technical conditions on $f$ used in the literature are relaxed. The KKM technique is used to generalize and unify some exist...

A Complex Search Technique for Solving the Quadratic Assignment Problem

An algorithm recently developed by Enkhbat et al. [3] based on continuous relaxation of the quadratic assignment problem generates suboptimal solution of good quality on average giving no sufficient enough verification on global optimality of the generated solution, whereas a branch and bound method provides a solution with verified global optimality, taking on input an upper bound close to glo...