The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We generalize the standard Arrow-d'Aspremont-Gerard-Varet (AGV) mechanism to balance the (ex-ante) net payoffs received by all agents, while maintaining Bayesian incentive compatibility, ex-post efficiency, and ex-post budget balance of the standard AGV mechanism. In a private-value environment with independent agents' types and the principal's cost, we show (under mild conditions) the existence of...
When using the standard particle swarm optimization to optimize the complex problems with high dimension, low convergence efficiency and falling into local optimization usually occur because of its inherent disadvantages. To avoid these disadvantages, a novel hybrid particle swarm optimization improved by mutative scale chaos method is proposed in this paper. This hybrid algorithm combines global...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.