Energy saving heuristics in Backbone Networks

The paper presents an approach aimed to reduce the overall power consumption of a backbone network by exploiting the power behavior of green network devices. This approach is based on the solution of an optimization problem that has a Mixed Integer NonLinear Programming (MINLP) formulation. Given that the problem is NP-hard, exact methods for finding optimal solutions can be used only for scenarios of limited size. To cope with the case of complex networks, the paper proposes two variations of the Fast Greedy Heuristic (FGH), denoted as Time Limited PAR Heuristic (TLPH) and PAR Meta Heuristic (PMH). The simulation study highlights the capability of the proposed heuristics to obtain solutions near the optimum and to outperform the other approaches in terms of power savings and CPU times needed to find a solution in complex network scenarios

An FPTAS for a General Class of Parametric Optimization Problems

Lecture Notes in Computer Science book series (LNCS, volume 11653)In a (linear) parametric optimization problem, the objective value of each feasible solution is an affine function of a real-valued parameter and one is interested in computing a solution for each possible value of the parameter. For many important parametric optimization problems including the parametric versions of the shortest path problem, the assignment problem, and the minimum cost flow problem, however, the piecewise linear function mapping the parameter to the optimal objective value of the corresponding non-parametric instance (the optimal value function) can have super-polynomially many breakpoints (points of slope change). This implies that any optimal algorithm for such a problem must output a super-polynomial number of solutions.We provide a (parametric) fully-polynomial time approximation scheme for a general class of parametric optimization problems for which (i) the parameter varies on the nonnegative real line, (ii) the non-parametric problem is solvable in polynomial time, and (iii) the slopes and intercepts of the value functions of the feasible solutions are nonnegative, integer values below a polynomial-time computable upper bound. In particular, under mild assumptions, we obtain the first parametric FPTAS for each of the specific problems mentioned above

Uncertain outcome presentations bias decisions: experimental evidence from Finland and Italy

Even in their everyday lives people are expected to make difficult decisions objectively and rationally, no matter how complex or uncertain the situation. In this research, we study how the format of presentation and the amount of presented information concerning risky events influence the decision-making process, and the propensity to take risk in decision makers. The results of an exploratory survey conducted in Finland and in Italy suggest that decision-making behavior changes according to the way the information is presented. We provide experimental evidence that different representations of expected outcomes create distinct cognitive biases and as a result affect the decisions made. This identified change in the perception of risk has, to the best of our knowledge, not been identified nor directly studied previously in the scientific literature. The paper thus presents novel insights into managerial decision-making that are potentially relevant for decision support theory, with implications to decision-makers and for information providers. Understanding the impact of various forms of presentation of risk is crucial in being able to convey information clearly and in a way that avoids misunderstandings. The implications of the results on being able to avoid opportunistic manipulation of decisions, are also of great concern in many application areas. Social networks are more and more frequently being used as a source of information and in this context it is crucial to acknowledge the effect that different ways of presenting and communicating risky outcomes may have on the behavior of the target group. Here presented results may, for example, be highly relevant for marketing and advertising that is conducted by using social media or social networks