Optimal Efficiency Guarantees for Network Design Mechanisms*
... using approximation measures. This approach can be applied equally well to cost-sharing mechanism design, and allows us to quantify the inevitable efficiency loss in incentive-compatible, budget-balanced cost-sharing mechanisms. As worst-case approximation measures are rarely used in economics, this ...
... using approximation measures. This approach can be applied equally well to cost-sharing mechanism design, and allows us to quantify the inevitable efficiency loss in incentive-compatible, budget-balanced cost-sharing mechanisms. As worst-case approximation measures are rarely used in economics, this ...
AMPLITUDE EQUATIONS CLOSE TO A TRIPLE
... equations constitute a dynamical system of great interest from the point of view of the bifurcation theory. It is complex enough to give rise to new or not well known spatio-temporal dynamics, but, since it is two-dimensional, it can still be deeply explored from numerical simulations for small aspe ...
... equations constitute a dynamical system of great interest from the point of view of the bifurcation theory. It is complex enough to give rise to new or not well known spatio-temporal dynamics, but, since it is two-dimensional, it can still be deeply explored from numerical simulations for small aspe ...
Full Text
... ABMS, in which the agents have knowledge of their user preferences. A novel scheduling algorithm is also outlined by the author. In their literature, architecture of the meeting scheduling agent is described. This literature provides basic requirement and guide in developing an ABMS. Some researcher ...
... ABMS, in which the agents have knowledge of their user preferences. A novel scheduling algorithm is also outlined by the author. In their literature, architecture of the meeting scheduling agent is described. This literature provides basic requirement and guide in developing an ABMS. Some researcher ...
Sensitivity Analysis of Optimal Control Problems with Bang–Bang
... which precludes the application to bang–bang or singular controls. Here, we focus attention on optimal control problems with bang–bang controls. Recently, Agrachev et al. [1] have developed second–order sufficient conditions (SSC) for bang–bang controls which are stated in terms of an associated fin ...
... which precludes the application to bang–bang or singular controls. Here, we focus attention on optimal control problems with bang–bang controls. Recently, Agrachev et al. [1] have developed second–order sufficient conditions (SSC) for bang–bang controls which are stated in terms of an associated fin ...
A VEHICLE ROUTING PROBLEM WITH STOCHASTIC TRAVEL
... The ACO algorithm is a stochastic optimization algorithm specifically intended to solve discrete optimization problems, like the above described VRP. The inspiration of the ACO algorithm comes from the observation of the trail laying and the trail following behavior of a real ant species (Linepithae ...
... The ACO algorithm is a stochastic optimization algorithm specifically intended to solve discrete optimization problems, like the above described VRP. The inspiration of the ACO algorithm comes from the observation of the trail laying and the trail following behavior of a real ant species (Linepithae ...
Solvability of Some Nonlinear Fourth Order Boundary Value Problems
... / f (∂Ω) . The Brouwer degree (see [3]), denoted by deg (f, Ω, p) , assigns the “topological” number of solutions of the equation f (x) = p in the domain Ω to the map f. If the map f is continuously differentiable and such that the Jacobian Jf (x) 6= 0 for any x in the preimage f −1 (p), then the de ...
... / f (∂Ω) . The Brouwer degree (see [3]), denoted by deg (f, Ω, p) , assigns the “topological” number of solutions of the equation f (x) = p in the domain Ω to the map f. If the map f is continuously differentiable and such that the Jacobian Jf (x) 6= 0 for any x in the preimage f −1 (p), then the de ...
Numerical Methods
... We have an estimate of the error Use this to form a termination condition that requires ...
... We have an estimate of the error Use this to form a termination condition that requires ...
Multiple-criteria decision analysis
Multiple-criteria decision-making or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly considers multiple criteria in decision-making environments. Whether in our daily lives or in professional settings, there are typically multiple conflicting criteria that need to be evaluated in making decisions. Cost or price is usually one of the main criteria. Some measure of quality is typically another criterion that is in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider. It is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, we are interested in getting high returns but at the same time reducing our risks. Again, the stocks that have the potential of bringing high returns typically also carry high risks of losing money. In a service industry, customer satisfaction and the cost of providing service are two conflicting criteria that would be useful to consider.In our daily lives, we usually weigh multiple criteria implicitly and we may be comfortable with the consequences of such decisions that are made based on only intuition. On the other hand, when stakes are high, it is important to properly structure the problem and explicitly evaluate multiple criteria. In making the decision of whether to build a nuclear power plant or not, and where to build it, there are not only very complex issues involving multiple criteria, but there are also multiple parties who are deeply affected from the consequences.Structuring complex problems well and considering multiple criteria explicitly leads to more informed and better decisions. There have been important advances in this field since the start of the modern multiple-criteria decision-making discipline in the early 1960s. A variety of approaches and methods, many implemented by specialized decision-making software, have been developed for their application in an array of disciplines, ranging from politics and business to the environment and energy.