and Applied Analysis 3 the multivalued projection for K; (2) ∇g ⋆ (] 󸀠 ) ∈ K : ⟨∇g ⋆ (] 󸀠 ) − x, ∇g ⋆ (ω 󸀠 )

In this paper, we introduce two iterative schemes by a modified Krasnoselskii-Mann algorithm for finding a common element of the set of solutions of equilibrium problems and the set of fixed points of multivalued nonexpansive mappings in Hilbert space. We prove that the sequence generated by the proposed method converges strongly to a common element of the set of solutions of equilibruim proble...

In the last decade, there have been many papers dealing with second-order multivalued boundary value problems. We mention the works of Erbe and Krawcewicz [5, 6], Frigon [7, 8], Halidias and Papageorgiou [9], Kandilakis and Papageorgiou [11], Kyritsi et al. [12], Palmucci and Papalini [17], and Pruszko [19]. In all the above works, with the exception of Kyritsi et al. [12], p = 2 (linear differ...

Abstraction mappings are one of the major tools used to construct correctness proofs for concurrent algorithms. Several examples are given of situations in which it is useful to allow the abstraction mappings to be muttivalued. The examples involve algorithm optimization, algorithm distribution, and proofs of time bounds.

In this paper we prove some new fixed point theorems for multivalued mappings on orbitally complete uniform spaces.

in this paper, we introduce the (g-$psi$) contraction in a metric space by using a graph.let $f,t$ be two multivalued mappings on $x.$ among other things, we obtain a common fixedpoint of the mappings $f,t$ in the metric space $x$ endowed with a graph $g.$

We study the class coNPMV of complements of NPMV functions. Though defined symmetrically to NPMV, this class exhibits very different properties. We clarify the complexity of coNPMV by showing that it is essentially the same as that of NPMVNP. Complete functions for coNPMV are exhibited and central complexity-theoretic properties of this class are studied. We show that computing maximum satisfyi...

With this paper we present a Multivalued Evolutionary Algorithm (MEA) which is inspired by fuzzy set theory. The genetic representation and encoding is done in such a way that no inferences can be drawn from phenotype to genotype. This representation innuences the used genetic operators. The basic operators of the algorithm will be explained and comparisons for global optimization problems with...