The results presented in the thesis show how to convert a statistically binding but computationally concealing quantum bit commitment scheme into a computationally binding but statistically concealing scheme. For a security parameter n, the construction of the statistically concealing scheme requires O(n) executions of the statistically binding scheme. As a consequence of the reduction, statist...

In this paper we present a promising technique that enhances the efficiency of GAs, when they are applied to constrained optimisation problems. According to this technique, the problem constraints are included in the fitness function as penalty terms, that vary during the GA evolution, facilitating thus the location of the global optimum and the avoidance of local optima. Moreover we proceed to...

This paper focuses on the state-of-the-art of unit commitment (UC) and economic dispatch (ED) algorithms suitable for Italian electricity market. In view spread renewable energy systems (RES), desired UC algorithm should be able to properly consider uncertainty affecting key input variables into formulation problem, as well different capabilities dispatched power plants provide ancillary servic...

We explicitly show the upper bound on the round complexity for perfectly concealing bit commitment schemes based on the general computational assumption. The best known scheme in the literature is the one-way permutation based scheme due to Naor, Ostrovsky, Venkatesan and Yung and its round complexity is O(n). We consider a naive parallel version of their scheme of the multiplicity logn and obt...

We present a very practical string-commitment scheme which is provably secure based solely on collision-free hashing. Our scheme enables a computationally bounded party to commit strings to an unbounded one, and is optimal (within a small constant factor) in terms of interaction, communication, and computation. Our result also proves that constant round statistical zero-knowledge arguments and ...

The Chance-Constrained Stochastic Programming (CCSP) is one of the models for decision making under uncertainty. In this paper, we consider the special case of the CCSP in which only the righthand side vector is random with a discrete distribution having a finite support. The unit commitment problem is one of the applications of the special case of the CCSP. Existing methods for exactly solving...