Source-to-source architecture transformation for performance optimization in BIP
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This paper studies the flight path planning problem for a large-scale air traffic management (ATM) system. The goal is to find the optimal 4D path plan, represented by a sequence of waypoints and the corresponding time stamps, for each individual flight su ...
Scala is a new programming language bringing together object-oriented and functional programming. Its defining features are uniformity and extensibility. Scala offers great flexibility for programmers, allowing them to grow the language through libraries. ...
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State machine replication is a technique for making services fault-tolerant by replicating them over a group of machines. Although the theory of state machine replication has been studied extensively, the engineering challenges of converting a theoretical ...
BIP (Behavior, Interaction, Priorities) is a component framework for constructing systems from a set of atomic components by using two kinds of composition operators: interactions and priorities.In this paper we present a method that transforms the interac ...
Uncertainty Feature Optimization is a framework to cope with optimization problems due to noisy data, using an implicit characterazation of the noise. The Aircraft Scheduling Problem (ASP) is a particular case of such problems, where disruptions randomly p ...
In the framework of process optimization, the use of measurements to compensate the effect of uncertainty has re-emerged as an active area of research. One of the ideas therein is to adapt the inputs in order to track the active constraints and push certai ...
In this paper, we present an application to the Airline Scheduling Problem (ASP) of the Uncertainty Feature Optimization (UFO) framework which combines both a proactive scheduling algorithm and a reactive recovery algorithm used for re-optimization when di ...
In this paper, we present an application to the Airline Scheduling Problem (ASP) of the Uncertainty Feature Optimization (UFO) framework which combines both a proactive scheduling algorithm and a reactive recovery algorithm used for re-optimization when di ...