In recent years, significant progress has been made in the field of distributed optimization algorithms. This study focused on convex problem over an undirected network. The target was to minimize average all local objective functions known by each agent while communicates necessary information only with its neighbors. Based state-of-the-art algorithm, we proposed a novel when function satisfie...

To solve the multimodal transport route optimization problem considering carbon emission, vehicle speed has time-varying characteristics, and customer a time window limit. The emission of system is affected by energy consumption vehicles in network. network uncertain, emissions may continue to rise after gradual decline. Based on this, this study established sum cost, transportation penalty cos...

We study the computability and complexity of the exploration problem in a class of highly dynamic networks: carrier graphs, where the edges between sites exist only at some (unknown) times defined by the periodic movements of mobile carriers among the sites. These graphs naturally model highly dynamic infrastructure-less networks such as public transportswith fixed timetables, lowearth orbiting...

This paper presents a novel multi objective model for optimizing the purchase decision of a cloud computing services customer. The providers are typically offering consumers cloud computing varying information systems services. The cloud services consist of different functionalities at varying costs, and varying reliability. So the customer’s main objectives (based on the literature) are to max...

fuzzy time series have been developed during the last decade to improve the forecast accuracy. many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. in this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly effici...

This paper considers the problem of real-time mode scheduling in linear time-varying switched systems subject to a quadratic cost functional. The execution time of hybrid control algorithms is often prohibitive for real-time applications and typically may only be reduced at the expense of approximation accuracy. We address this trade-off by taking advantage of system linearity to formulate a pr...

This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the pe...