Ludovica Adacher

Autonomous agents architectures and algorithms in flexible manufacturing systems

This paper investigates possible implementations of the autonomous agents concept in flexible manufacturing control. The implementation issues and the effectiveness of different control architectures and algorithms are analyzed by means of a simulation model of a flexible job shop. Extensive experimental results are reported, allowing the evaluation of the trade-off between the degree of autonomy and system performance.

Situation awareness in critical infrastructures

Critical infrastructure(CI) protectionand situationawarenessarerelevanttopicsin critical system domain. These issuesgofarbeyond the academicworldinvolvingvery often the national security framework. In this contribution, a review of the most attractive approaches proposed for addressing the situation awareness problems is presented. Most of the proposed approaches are based on multi-sensor data fusion, since the awareness is achieved by building a scenario using data providedby sensors spread into the systems. Humans are supposed to interact with the system, but only a few models are able to include their intervention. The review analysis is performed by considering models, architectures, and techniques adopted in each system and by highlighting their effectiveness and drawbacks. Finally an example in the field of air traffic management is presented.

AN AGENT BASED APPROACH TO THE REAL TIME AIR TRAFFIC CONTROL

Abstract Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major factors is the limited operative capacity of the air network. In this work an agent based approach to the real time air traffic control is proposed. The air network is considered partitioned in different sectors. Each sector has its own decision agent devoted to the air traffic control involved in. In each of these sectors, in order to guarantee the respect of both delay and capacity constraints, a real time scheduling of the flights is obtained by an iterative procedure based on a specific graph model.

Aircraft Ground Routing and Scheduling Optimization

In this paper we deal with the ground optimization problem, that is the problem of routing and scheduling airplanes surface maneuvering operations. We consider the specific case study of Malpensa Terminal Maneuvering Area (Italy). Our objective function is the minimization of total tardiness. At first a routing problem is solved to assign a path to each aircraft in the terminal, then the scheduling problem of minimizing the average tardiness is addressed. We model the scheduling problem as a job-shop scheduling problem. We develop heuristic procedures based on the alternative graph formulation of the problem to construct and improve feasible solutions. Experimental results based on real data and analysis are reported.

Limiting pollution in ground control optimization

In this paper we deal with the problem of scheduling aircrafts maneuvering on ground in the specific case study of Malpensa Airport. Given a fixed route and a landing/take off time instant for each landing/departing aircraft, we consider three objective functions in the following lexicographical order: (i) the minimization of the number of tardy aircrafts; (ii) the maximization of the safety; (iii) the minimization of pollution and noise. Problem constraints are related to the safety rules. We model the problem as a job-shop scheduling problem. We develop heuristic procedures based on an alternative graph formulation of the problem to construct and improve feasible solutions. Experimental results based on real data and analysis are reported.

A New Methodology to Calibrate the Congestion Wave for the Cell Transmission Model for Urban Traffic

This paper presents a new traffic flow model to capture complex urban traffic dynamics. We present an extension of the Cell Transmission Model for Urban Traffic (CTM-UT). It is suitable to represent complex flow interactions among lane groups at upstream of signalized intersections and at intersection with determination capacity. Our model is a simple and versatile simulation framework designed to realistically simulate the dynamic queue interactions. It can represent the potential capacity of minor flow obstructed at intersection for large scale urban network. In this paper we present our macroscopic simulation model considering also an optimization calibration method for congestion wave. A comparison between our model and Simulation of Urban MObility (SUMO) is done.

Stochastic Optimization for Macroscopic Urban Traffic Model with Microscopic Elements

The Cell Transmission Model for Urban Traffic (CTM-UT) is a macroscopic model with microscopic traffic elements for complex traffic dynamics of arterial and node. In this paper we presented the surrogate method (SM) to optimize the signal synchronization problem considering every turns in accord with the CMT-UT framework. Some extensions to improve the efficiency and efficacy of the surrogate method are proposed. Preliminarily experiments indicate that the CTM-UT can be well-applied for the signal synchronization of realtime urban traffic with good trade-off of efficiency respect to a macroscopic model.

Decentralized Assignment for Intelligent Electric Vehicles to Recharge Stations

In this paper the problem of assigning electric cars to charging stations in a distributed manner is addressed, resorting to Lagrangian-based distributed algorithms. Within such algorithms, the routing process is the result of a cooperation among several decision makers, having each one a local knowledge of the system. The decision makers are in charge to decide the type of information to be exchanged. Our focus is to investigate the performance of different algorithms based on different knowledge degrees of the system. The implementation issues and the effectiveness of the algorithms are analysed via simulation. The trade-off between knowledge degree and system performance is currently under study.

Comparing Lagrangian-based distributed algorithms for parallel machine scheduling problems

In this paper Lagrangian-based distributed algorithms for scheduling jobs on unrelated parallel machines are presented. In these algorithms, the scheduling process is the result of a cooperation process among several Decision Makers (DMs). DMs have a local knowledge of the system, and the possibility to decide which type of information to exchange each other. Our focus is to investigate the performance of different algorithms based on different knowledge degrees of the parallel machine system. The implementation issues and the effectiveness of the algorithms are analysed via simulation, in which problem instances with job dynamic arrivals are also considered.

A macroscopic model with the advantages of microscopic model: A review of Cell Transmission Model’s extensions for urban traffic networks

Abstract This paper reports a review of the extensions and application of the Cell Transmission Model (CTM). Those extensions are models able to simulate complex urban traffic dynamics with all the advantages of macroscopic and microscopic urban traffic model. Over the past few years researchers have been trying to increase the level of detail by extending CTM and introducing new formulations to improve the application of the model in urban traffic. The authors classified the papers while taking into consideration all those factors characterizing the urban traffic, arterial and intersection traffic flow in particular. One of the primary goals of transport research is to develop a general framework of urban traffic networks that might be applied from a realistic point of view. Recent studies about traffic simulations have shown that, among various macroscopic simulation models, the CTM has the potential to achieve this objective. We have also reported our model the CTM_UT that improves the CTM for Urban Traffic. We believe that it is possible to apply this model to ITS application, hence increase the accuracy of the macroscopic model while maintaining the computational advantages and provide an accurate prediction of travel time approach.