Giuseppe Confessore

A Network Based Model for Traffic Sensor Location with Implications on O/D Matrix Estimates

In this paper, we define and solve the sensor location problem (SLP), that is, we look for the minimum number and location of counting points in order to infer all traffic flows in a transport network. We set up a couple of greedy heuristics that find lower and upper bounds on the number of sensors for a set of randomly generated networks. We prove that solving the SLP implies that the Origin/Destination (O/D) matrix estimation error be always bounded. With respect to alternative sensor location strategies, simulation experiments show that: (i) measurement costs being equal, the O/D estimation error is lower, and (ii) conversely, O/D estimation error being equal, the number of sensors is smaller.

A market-based multi-agent system model for decentralized multi-project scheduling

We consider a multi-project scheduling problem, where each project is composed of a set of activities, with precedence relations, requiring specific amounts of local and shared (among projects) resources. The aim is to complete all the project activities, satisfying precedence and resource constraints, and minimizing each project schedule length. The decision making process is supposed to be decentralized, with as many local decision makers as the projects. A multi-agent system model, and an iterative combinatorial auction mechanism for the agent coordination are proposed. We provide a dynamic programming formulation for the combinatorial auction problem, and heuristic algorithms for both the combinatorial auction and the bidding process. An experimental analysis on the whole multi-agent system model is discussed.

A network flow based heuristic approach for optimising AGV movements

Automated Guided Vehicles (AGVs) are driverless carriers that automatically navigate along planned paths by means of several guidance and control methods. This paper proposes an approach for solving the dispatching problem in an AGV system. The problem is modelled through a network by relying on the formulation of a Minimum Cost Flow Problem. In the defined graph, the nodes represent transportation tasks and AGVs while the arcs consider, through the associated weights, several system’s aspects such as pick, drop, and travel times, battery recharging, capacity constraints, congestion and error issues. Two objectives can be achieved: (i) minimisation of the average time for carrying out transportation tasks or (ii) maximisation of the utilisation degree of AGVs. The modelling and solution approach adopted has provided a novel Vehicle–Initiated dispatching rule and parameters settings for the dynamic assignments of transportation missions to AGVs. The decision making process concurrently and dynamically considers several factors. The results show a relevant reduction in the average time for transportation order fulfilment and a decrease in its variability. The proposed approach has been exploited for optimising the AGVs performance in a pharmaceutical production system.

A simulation-based approach for estimating the commercial capacity of railways

Rail transport is expected to play a remarkable role for a sustainable mobility in Europe. This paper presents an approach for estimating the commercial capacity of railways. The commercial capacity is intended as the number of possible paths in a defined time window on a rail line, or part of it, considering a fixed path mix, with market-oriented quality. The capacity management is one of the most important tasks of railway Infrastructure Managers. The proposed simulation-based approach relies on the use of an optimizer and a simulator. The study has been developed for the rail line Verona-Brennero, located in the Italian part of the European Corridor Hamburg-Napoli. Computational results allowed to estimate the commercial capacity differences between the whole line and three important line sections within it. Other computational experiments showed the relevant estimated increase in commercial capacity that a reduction in time spacing between trains could imply.

An approximation result for a periodic allocation problem

In this paper we study a periodic allocation problem which is a generalization of the dynamic storage allocation problem to the case in which the arrival and departure time of each item is periodically repeated. These problems are equivalent to the interval coloring problem on weighted graphs in which each feasible solution corresponds to an acyclic orientation, and the solution value is equal to the length of the longest weighted path of the oriented graph. Optimal solutions correspond to acyclic orientations having the length of longest weighted path as small as possible. We prove that for the interval coloring problem on a class of circular arc graphs, and hence for a periodic allocation problem, there exists an approximation algorithm that finds a feasible solution whose value is at most two times the optimal.

Development of a Multi-Agent Model for Production Scheduling in Innovative Flexible Manufacturing System

The reduction of a Manufacturing System Complexity is possible adopting a decentralized approach focused on optimization at operation level, and on coordination at higher level of production plant. This point of view, inherited by multi agent models, can increase the flexibility and reduce the complexity of the system management. We apply this principle to a shoe manufacturing system, characterized by an automated transportation who, governed by scheduling rules, can exploit the overtake capability. The operational objectives of the plant are to augment the capacity of the system, to rapidly react to market changes and to obtain a better balance machine work load.

A simulation-based architecture for supporting strategic and tactical decisions in the apron of Rome-Fiumicino Airport

In this paper, we describe an architecture for the evaluation and optimization of aircraft ground movements in apron taxiways. The paper aims at providing an effective methodology for supporting the decision-makers involved in both the apron design and management phases. The purpose deriving from the utilization of the proposed approach consists in obtaining substantial improvements in the level of service with a reduction in congestion and ground delays within airports while considering safety aspects like aircraft separation. The methodology relies on a modular architecture. A simulation-based architecture, in which an optimization module is included, has been developed; an information feedback between simulation and optimization modules is enabled. The validation has been performed through the data of the apron of Rome-Fiumicino airport. The computational results show a reduction in aircraft flowtime and a relevant decrease in aircraft ground flows. Interesting issues related to strategic modification of system configuration are presented.

An approximation result for the interval coloring problem on claw-free chordal graphs

We study the problem of finding an acyclic orientation of an undirected graph, such that each (oriented) path is covered by a limited number k of maximal cliques. This is equivalent to finding a k-approximate solution for the interval coloring problem on a graph. We focus our attention on claw-free chordal graphs, and show how to find an orientation of such a graph in linear time, which guarantees that each path is covered by at most two maximal cliques. This extends previous published results on other graph classes where stronger assumptions were made.

WiFi Assisted GPS for Extended Location Services

This paper shows a lightweight technique for extending the positioning capabilities of a global navigation satellite system to areas characterized by reduced satellite visibility. This technique includes the presence of a WiFi coverage, used to implement the virtual satellite concept. In particular we assume that a customer terminal can receive both Global Positioning System (GPS) signals and WiFi beacons broadcasted by an access point (AP). We show that if such beacons include the geo-referenced position of the relevant AP, the suitable usage of this information allows determining the GPS receiver position even if only three satellites are visible. Experimental results show that the achievable performance are similar to that obtainable by a plain GPS receiver using four visible satellites.

An Evolutionary Algorithm for Vehicle Routing Problem with Real Life Constraints

Real life distribution problems present high degree of complexity mostly derived by the need to respect a variety of constraints. Moreover they are not considered by the classical models of the vehicle routing literature. In this paper we consider a vehicle routing problem with heterogeneous vehicle fleet with different capacity, multi-dimensional capacity constraints, order/vehicle, item/vehicle, and item/item compatibility constraints, different start and end locations for vehicles, and multiple time windows restrictions. We propose an evolutionary algorithm based on the combination of a genetic algorithm and local search heuristics. We investigated the performance of the implemented algorithm in the large-scale retail and in the waste collection industries.