Mauro Dell'Orco | Politecnico di Bari (original) (raw)

Papers by Mauro Dell'Orco

Procedia - Social and Behavioral Sciences, Feb 1, 2014

A crucial step in transportation planning process is the measure of systems efficiency. Many effo... more A crucial step in transportation planning process is the measure of systems efficiency. Many efforts have been made in this field in order to provide satisfactory answer to this problem. One of the most used methodologies is the Data Envelopment Analysis (DEA) that has been applied to a wide number of different situations where efficiency comparisons are required. The DEA technique is a useful tool since the approach is non-parametric, and can handle many output and input at the same time. In a lot of real applications, input and output data cannot be precisely measured. Imprecision (or approximation) may be originated from indirect measurements, model estimation, subjective interpretation, and expert judgment of available information. Therefore, methodologies that allow the analyst to explicitly deal with imprecise or approximate data are of great interest, especially in freight transport where available data as well as stakeholders' behavior often suffer from vagueness or ambiguity. This is particularly worrying when assessing efficiency with frontier-type models, such as Data Envelopment Analysis (DEA) models, since they are very sensitive to possible imprecision in the data set. The specification of the evaluation problem in the framework of the fuzzy set theory allows the analyst to extend the capability of the traditional "crisp" DEA to take into account and, thus, to represent the uncertainty embedded in real life problems. The existing fuzzy approaches are usually categorized in four categories: a) the tolerance approaches; b) the defuzzification approaches c) thelevel based approaches; d) the fuzzy ranking. In this paper, we have explored the Fuzzy Theory-based DEA model, to assess efficiency measurement for transportation systems considering uncertainty in data, as well as in the evaluation result. In particular, the method is then applied to the evaluation of efficiency of container ports on the Mediterranean See with a sensitivity analysis in order to investigate the properties of the different approaches. The results are then compared with traditional DEA.

Optimum routeing for a public transport system is a choice amongst various possibilities extendin... more Optimum routeing for a public transport system is a choice amongst various possibilities extending between the two extreme cases of: direct connections between all the modes of the network; and a single itinerary which connects all the modes. The first solution, referred to as the "simultaneous network", provides quicker transport but is more costly to operate. The second, referred to as the "cycle", is less costly but gives poorer service to the user. This article presents a multicriteria analysis for determining a good compromise solution between the profitability interests of the operator and the level of service required by the user.

2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)

In recent years, maritime freight transportation and the consequent handling of containers are am... more In recent years, maritime freight transportation and the consequent handling of containers are among the most dynamic and growing sectors. The aim of this research is to propose a Decision Support System (DSS) addressed mainly to shipping companies, allowing the choice, even en-route, of the hub port of destination for the successive multi-modal operations. The companies make choices in relation both to the ship location and to a dynamic accessibility indicator. The accessibility indicator is generally accepted as the parameter that better represents the interactions between a port and its hinterland. Different factors can influence the accessibility in maritime transport; some of them are characterized by low variability, while others show a high within-day dynamics. For example, the technical characteristics of ports (number of berths and their depths, number of cranes, storage area, etc.) belong to the first group; instead, the number of free berths, the delay time in freight loading and unloading operations, and weather conditions can change during the day. Their variability can be evaluated by a real-time monitoring, while the ship location can be easily obtained by GPS and radar signals. In the proposed DSS, we have considered data about the technical characteristics of ports and, depending on the request coming from ships, acquires the dynamic characteristics of each port, the ship location and the destination area. After the completion of the process, the DSS provides as output the port “closer” to the requests expressed by the users. Since some current values of both the dynamic characteristics of ports and information provided by shipping companies are subject to uncertainty, we proposed a DSS based on a multivariate accessibility indicator.

Transportation Research Procedia, 2017

The aim of this paper is to evaluate the best mode of transport in relation to the transport qual... more The aim of this paper is to evaluate the best mode of transport in relation to the transport quality perceived by users. To this aim, we have found a framework to aggregate data and information coming from multiple information sources, often characterized by a high level of uncertainty. The proposed method is a hybrid approach based on two different theories: the Analytical Hierarchy Process (Saaty, 1980) and the Evidence-or Dempster-Shafer-Theory(Dempster 1967; 1968; Shafer, 1976). First, we have carried out a survey to investigate the users' point of view about the quality of transport, expressed through fifteen criteria, representative of the transport quality. Within the survey, the users were asked to rank the chosen criteria. Due to the complexity of the transport problem, we have used the Analytical Hierarchy Process to decompose the problem in different levels. Because of the decomposition, we have obtained priority vectors, which we have taken as basic probability assignments for application of the Dempster-Shafer Theory (DST). The DST is used to fuse different users' opinions and to take into account Uncertainty embedded in human judgment. The results show which alternatives users consider the best in relation to analyzed criteria.

2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2015

A bi-level simulation model was developed to forecast pedestrians evacuation time of large areas.... more A bi-level simulation model was developed to forecast pedestrians evacuation time of large areas. The simulation system provides two levels: microscopic and mesoscopic. Both levels' dynamics have been modelled using the fuzzy inference system, in order to incorporate the fuzzy perception and anxiety embedded in human reasoning. At the mesoscopic level, pedestrians are organized in different groups generating a particle flow with a certain density. Pedestrian representation switches from mesoscopic to microscopic level at a threshold distance from exit. An application software was developed to evaluate the outcomes of the model. The model was tested in scenarios with presence of fixed obstacles. Simulation results and computational performances are promising.

Transportation Research Procedia, 2017

Intelligent transportation systems (ITS) work by collections of data in real time. Average speed,... more Intelligent transportation systems (ITS) work by collections of data in real time. Average speed, travel time and delay at intersections are some of the most important measures, often used for monitoring the performance of transportation systems, and useful for system management and planning. In urban transportation planning, intersections are usually considered critical points, acting as bottlenecks and clog points for urban traffic. Thus, detecting the travel time at intersections in different turning directions is an activity useful to improve the urban transport efficiency. Smartphones represent a low-cost technology, with which is possible to obtain information about traffic state. However, smartphone GPS data suffer for low precision, mainly in urban areas. In this paper, we present a fuzzy set-based method for car positioning identification within road lanes near intersections using GPS data coming from smartphones. We have introduced the fuzzy sets to take into account uncertainty embedded in GPS data when trying to identify the position of cars within the road lanes. Moreover, we introduced a Genetic Algorithm to calibrate the fuzzy parameters in order to obtain a novel supervised clustering technique. We applied the proposed method to one intersection in the urban road network of Bari (Italy). First results reveal the effectiveness of the proposed methodology when comparing the outcomes of the proposed method with two well-known clustering techniques (Fuzzy C-means, K-means).

Transportation Research Part C: Emerging Technologies, 2016

Abstract In this article, we propose a framework for travel time prediction based on a time-discr... more Abstract In this article, we propose a framework for travel time prediction based on a time-discrete, mesoscopic traffic flow model, in which the measure of travel time is obtained as a link performance resulting from a dynamic network loading process. The spatiotemporal flow propagation on the road network is simulated incorporating the mesoscopic model and a linear link performance model, based on a travel time function. Acceleration levels are calculated explicitly, as a result of a fixed point problem. The traffic assignment to the network has been carried out through a completely new model, based on the Bee Colony Optimization (BCO) metaheuristics. In comparison with results of simulations carried out by using another mesoscopic model (DYNASMART), the travel times obtained with the proposed method appear more realistic.

Proceedings of the Seventh International Conference on Enterprise Information Systems, 2005

Optimization of Life Cycle Cost (LCC) in railroad maintenance, is one of the main goals of the ra... more Optimization of Life Cycle Cost (LCC) in railroad maintenance, is one of the main goals of the railways managers. In order to achieve the best balance between safety and operating costs, "on condition" maintenance is more and more used; that is, a maintenance intervention is planned only when and where necessary. Nowadays, the conditions of railways are monitored by means of special diagnostic trains: these trains, such as Archimede, the diagnostic train of the Italian National Railways, allow to observe every 50 cm dozens of rail track characteristic attributes simultaneously. Therefore, in order to plan an effective on condition maintenance, managers have a large amount of data to be analyzed through an appropriate Decision Support System (DSS). However, even the most up-to-date DSSs have some drawbacks: first of all, they are based on a binary logic with rigid thresholds, restricting their flexibility in use; additionally, they adopt considerable simplifications in the rail track deterioration model. In this paper, we present a DSS able to overcome these drawbacks. It is based on fuzzy logic and it is able to handle thresholds expressed as a range, an approximate number or even a verbal value. Moreover, through artificial neural networks it is possible to obtain more likely the rail track deterioration models. The proposed model can analyze the data available for a given portion of rail-track and then it plans the maintenance, optimizing the available resources.

PROMET - Traffic&Transportation, 2018

For a long time, many researchers have investigated the continuous network design problem (CNDP) ... more For a long time, many researchers have investigated the continuous network design problem (CNDP) to distribute equitably additional capacity between selected links in a road network, to overcome traffic congestion in urban roads. In addition, CNDP plays a critical role for local authorities in tackling traffic congestion with a limited budget. Due to the mutual interaction between road users and local authorities, CNDP is usually solved using the bilevel modeling technique. The upper level seeks to find the optimal capacity enhancements of selected links, while the lower level is used to solve the traffic assignment problem. In this study, we introduced the enhanced differential evolution algorithm based on multiple improvement strategies (EDEMIS) for solving CNDP. We applied EDEMIS first to a hypothetical network to show its ability in finding the global optimum solution, at least in a small network. Then, we used a 16-link network to reveal the capability of EDEMIS especially in t...

Transportation Research Part C: Emerging Technologies, 2017

In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' ... more In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users' changing perception of travel time also based on current network conditions. Drivers' choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.

The gate assignment problem (GAP) is one of the most important problems that operations managers ... more The gate assignment problem (GAP) is one of the most important problems that operations managers face daily. The GAP aims at determining an assignment of flights to terminal and ramp positions (gates), and an assignment of starting and ending times of the processing of a flight at its position. The objectives related to the flight gate assignment problem (FGAP) include the minimization of the number of flights assigned to remote terminals and the minimization of passengers’ total walking distance. The main aim of this research is to find a novel methodology to solve the FGAP. In this paper, we propose a hybrid approach called Biogeography-based Bee Colony Optimization (B-BCO). This approach is obtained by properly combining two metaheuristics: biogeography-based (BBO) and bee colony optimization (BCO) algorithms. The proposed B-BCO model integrates the BBO migration operator into to bee’s search behavior. The obtained results show the better performances of the proposed approach in ...

2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2020

Real-time information and software support systems are crucial points for performing efficient lo... more Real-time information and software support systems are crucial points for performing efficient logistics operations. Recently, most of the logistics companies have been using green-logistics solutions that encourage the use of eco-friendly vehicles, especially cargo bikes. However, for evaluating logistics' business performance, driver's exposure to emissions has often been neglected. Therefore, we proposed a Decision Support System (DSS) that considers, on the one hand, the efficiency of logistics performance and, on the other, the possibility of e-cargo bike drivers to choose the optimal route path considering two options, such as minimum travel time and minimum emission exposure. We applied the proposed DSS in a numerical application that evaluates the customer's assignment to an e-cargo bike according to the hourly traffic flows and emissions. We developed a dynamic algorithm that evaluates the path choice comparison between two route options. The choice of the minim...

IET Intelligent Transport Systems, 2018

Recently, several prominent logistic companies in Europe and the USA are seriously considering th... more Recently, several prominent logistic companies in Europe and the USA are seriously considering the idea of using drones launched from trucks and working in parallel to deliver packages. In the relevant literature, a novel problem formulation called travelling salesman problem with drone has been introduced, and some modelling and solution approaches have been presented. Existing approaches are based on the main assumption that the truck can dispatch and pick up a drone only at a node, i.e. the depot or a customer location. Here, the authors present a novel approach aimed to maximise the drone usage in parcel delivering. The authors consider that a truck can deliver and pick a drone up not only at a node but also along a route arc (en route). In this way, the operations of a drone are not strictly related to the customers' position, but it can serve a wider area along the route. The authors tested the proposed heuristic on benchmark instances and analysed the benefits introduced with the en route approach.

Transportation Research Procedia, 2018

Selection and peer-review under responsibility of the scientific committee of the EURO Mini Confe... more Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on "Advances in Freight Transportation and Logistics" (emc-ftl2018).

PROMET - Traffic&Transportation, 2018

For a long time, many researchers have investigated the continuous network design problem (CNDP) ... more For a long time, many researchers have investigated the continuous network design problem (CNDP) to distribute equitably additional capacity between selected links in a road network, to overcome traffic congestion in urban roads. In addition, CNDP plays a critical role for local authorities in tackling traffic congestion with a limited budget. Due to the mutual interaction between road users and local authorities, CNDP is usually solved using the bilevel modeling technique. The upper level seeks to find the optimal capacity enhancements of selected links, while the lower level is used to solve the traffic assignment problem. In this study, we introduced the enhanced differential evolution algorithm based on multiple improvement strategies (EDEMIS) for solving CNDP. We applied EDEMIS first to a hypothetical network to show its ability in finding the global optimum solution, at least in a small network. Then, we used a 16-link network to reveal the capability of EDEMIS especially in t...

Transportation Research Part C: Emerging Technologies, 2017

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of... more In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers' total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.

Transportation Research Part C: Emerging Technologies, 2017

In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' ... more In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users' changing perception of travel time also based on current network conditions. Drivers' choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.

Procedia - Social and Behavioral Sciences, Feb 1, 2014

A crucial step in transportation planning process is the measure of systems efficiency. Many effo... more A crucial step in transportation planning process is the measure of systems efficiency. Many efforts have been made in this field in order to provide satisfactory answer to this problem. One of the most used methodologies is the Data Envelopment Analysis (DEA) that has been applied to a wide number of different situations where efficiency comparisons are required. The DEA technique is a useful tool since the approach is non-parametric, and can handle many output and input at the same time. In a lot of real applications, input and output data cannot be precisely measured. Imprecision (or approximation) may be originated from indirect measurements, model estimation, subjective interpretation, and expert judgment of available information. Therefore, methodologies that allow the analyst to explicitly deal with imprecise or approximate data are of great interest, especially in freight transport where available data as well as stakeholders' behavior often suffer from vagueness or ambiguity. This is particularly worrying when assessing efficiency with frontier-type models, such as Data Envelopment Analysis (DEA) models, since they are very sensitive to possible imprecision in the data set. The specification of the evaluation problem in the framework of the fuzzy set theory allows the analyst to extend the capability of the traditional "crisp" DEA to take into account and, thus, to represent the uncertainty embedded in real life problems. The existing fuzzy approaches are usually categorized in four categories: a) the tolerance approaches; b) the defuzzification approaches c) thelevel based approaches; d) the fuzzy ranking. In this paper, we have explored the Fuzzy Theory-based DEA model, to assess efficiency measurement for transportation systems considering uncertainty in data, as well as in the evaluation result. In particular, the method is then applied to the evaluation of efficiency of container ports on the Mediterranean See with a sensitivity analysis in order to investigate the properties of the different approaches. The results are then compared with traditional DEA.

Optimum routeing for a public transport system is a choice amongst various possibilities extendin... more Optimum routeing for a public transport system is a choice amongst various possibilities extending between the two extreme cases of: direct connections between all the modes of the network; and a single itinerary which connects all the modes. The first solution, referred to as the "simultaneous network", provides quicker transport but is more costly to operate. The second, referred to as the "cycle", is less costly but gives poorer service to the user. This article presents a multicriteria analysis for determining a good compromise solution between the profitability interests of the operator and the level of service required by the user.

2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)

In recent years, maritime freight transportation and the consequent handling of containers are am... more In recent years, maritime freight transportation and the consequent handling of containers are among the most dynamic and growing sectors. The aim of this research is to propose a Decision Support System (DSS) addressed mainly to shipping companies, allowing the choice, even en-route, of the hub port of destination for the successive multi-modal operations. The companies make choices in relation both to the ship location and to a dynamic accessibility indicator. The accessibility indicator is generally accepted as the parameter that better represents the interactions between a port and its hinterland. Different factors can influence the accessibility in maritime transport; some of them are characterized by low variability, while others show a high within-day dynamics. For example, the technical characteristics of ports (number of berths and their depths, number of cranes, storage area, etc.) belong to the first group; instead, the number of free berths, the delay time in freight loading and unloading operations, and weather conditions can change during the day. Their variability can be evaluated by a real-time monitoring, while the ship location can be easily obtained by GPS and radar signals. In the proposed DSS, we have considered data about the technical characteristics of ports and, depending on the request coming from ships, acquires the dynamic characteristics of each port, the ship location and the destination area. After the completion of the process, the DSS provides as output the port “closer” to the requests expressed by the users. Since some current values of both the dynamic characteristics of ports and information provided by shipping companies are subject to uncertainty, we proposed a DSS based on a multivariate accessibility indicator.

Transportation Research Procedia, 2017

The aim of this paper is to evaluate the best mode of transport in relation to the transport qual... more The aim of this paper is to evaluate the best mode of transport in relation to the transport quality perceived by users. To this aim, we have found a framework to aggregate data and information coming from multiple information sources, often characterized by a high level of uncertainty. The proposed method is a hybrid approach based on two different theories: the Analytical Hierarchy Process (Saaty, 1980) and the Evidence-or Dempster-Shafer-Theory(Dempster 1967; 1968; Shafer, 1976). First, we have carried out a survey to investigate the users' point of view about the quality of transport, expressed through fifteen criteria, representative of the transport quality. Within the survey, the users were asked to rank the chosen criteria. Due to the complexity of the transport problem, we have used the Analytical Hierarchy Process to decompose the problem in different levels. Because of the decomposition, we have obtained priority vectors, which we have taken as basic probability assignments for application of the Dempster-Shafer Theory (DST). The DST is used to fuse different users' opinions and to take into account Uncertainty embedded in human judgment. The results show which alternatives users consider the best in relation to analyzed criteria.

2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2015

A bi-level simulation model was developed to forecast pedestrians evacuation time of large areas.... more A bi-level simulation model was developed to forecast pedestrians evacuation time of large areas. The simulation system provides two levels: microscopic and mesoscopic. Both levels' dynamics have been modelled using the fuzzy inference system, in order to incorporate the fuzzy perception and anxiety embedded in human reasoning. At the mesoscopic level, pedestrians are organized in different groups generating a particle flow with a certain density. Pedestrian representation switches from mesoscopic to microscopic level at a threshold distance from exit. An application software was developed to evaluate the outcomes of the model. The model was tested in scenarios with presence of fixed obstacles. Simulation results and computational performances are promising.

Transportation Research Procedia, 2017

Intelligent transportation systems (ITS) work by collections of data in real time. Average speed,... more Intelligent transportation systems (ITS) work by collections of data in real time. Average speed, travel time and delay at intersections are some of the most important measures, often used for monitoring the performance of transportation systems, and useful for system management and planning. In urban transportation planning, intersections are usually considered critical points, acting as bottlenecks and clog points for urban traffic. Thus, detecting the travel time at intersections in different turning directions is an activity useful to improve the urban transport efficiency. Smartphones represent a low-cost technology, with which is possible to obtain information about traffic state. However, smartphone GPS data suffer for low precision, mainly in urban areas. In this paper, we present a fuzzy set-based method for car positioning identification within road lanes near intersections using GPS data coming from smartphones. We have introduced the fuzzy sets to take into account uncertainty embedded in GPS data when trying to identify the position of cars within the road lanes. Moreover, we introduced a Genetic Algorithm to calibrate the fuzzy parameters in order to obtain a novel supervised clustering technique. We applied the proposed method to one intersection in the urban road network of Bari (Italy). First results reveal the effectiveness of the proposed methodology when comparing the outcomes of the proposed method with two well-known clustering techniques (Fuzzy C-means, K-means).

Transportation Research Part C: Emerging Technologies, 2016

Abstract In this article, we propose a framework for travel time prediction based on a time-discr... more Abstract In this article, we propose a framework for travel time prediction based on a time-discrete, mesoscopic traffic flow model, in which the measure of travel time is obtained as a link performance resulting from a dynamic network loading process. The spatiotemporal flow propagation on the road network is simulated incorporating the mesoscopic model and a linear link performance model, based on a travel time function. Acceleration levels are calculated explicitly, as a result of a fixed point problem. The traffic assignment to the network has been carried out through a completely new model, based on the Bee Colony Optimization (BCO) metaheuristics. In comparison with results of simulations carried out by using another mesoscopic model (DYNASMART), the travel times obtained with the proposed method appear more realistic.

Proceedings of the Seventh International Conference on Enterprise Information Systems, 2005

Optimization of Life Cycle Cost (LCC) in railroad maintenance, is one of the main goals of the ra... more Optimization of Life Cycle Cost (LCC) in railroad maintenance, is one of the main goals of the railways managers. In order to achieve the best balance between safety and operating costs, "on condition" maintenance is more and more used; that is, a maintenance intervention is planned only when and where necessary. Nowadays, the conditions of railways are monitored by means of special diagnostic trains: these trains, such as Archimede, the diagnostic train of the Italian National Railways, allow to observe every 50 cm dozens of rail track characteristic attributes simultaneously. Therefore, in order to plan an effective on condition maintenance, managers have a large amount of data to be analyzed through an appropriate Decision Support System (DSS). However, even the most up-to-date DSSs have some drawbacks: first of all, they are based on a binary logic with rigid thresholds, restricting their flexibility in use; additionally, they adopt considerable simplifications in the rail track deterioration model. In this paper, we present a DSS able to overcome these drawbacks. It is based on fuzzy logic and it is able to handle thresholds expressed as a range, an approximate number or even a verbal value. Moreover, through artificial neural networks it is possible to obtain more likely the rail track deterioration models. The proposed model can analyze the data available for a given portion of rail-track and then it plans the maintenance, optimizing the available resources.

PROMET - Traffic&Transportation, 2018

For a long time, many researchers have investigated the continuous network design problem (CNDP) ... more For a long time, many researchers have investigated the continuous network design problem (CNDP) to distribute equitably additional capacity between selected links in a road network, to overcome traffic congestion in urban roads. In addition, CNDP plays a critical role for local authorities in tackling traffic congestion with a limited budget. Due to the mutual interaction between road users and local authorities, CNDP is usually solved using the bilevel modeling technique. The upper level seeks to find the optimal capacity enhancements of selected links, while the lower level is used to solve the traffic assignment problem. In this study, we introduced the enhanced differential evolution algorithm based on multiple improvement strategies (EDEMIS) for solving CNDP. We applied EDEMIS first to a hypothetical network to show its ability in finding the global optimum solution, at least in a small network. Then, we used a 16-link network to reveal the capability of EDEMIS especially in t...

Transportation Research Part C: Emerging Technologies, 2017

In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' ... more In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users' changing perception of travel time also based on current network conditions. Drivers' choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.

The gate assignment problem (GAP) is one of the most important problems that operations managers ... more The gate assignment problem (GAP) is one of the most important problems that operations managers face daily. The GAP aims at determining an assignment of flights to terminal and ramp positions (gates), and an assignment of starting and ending times of the processing of a flight at its position. The objectives related to the flight gate assignment problem (FGAP) include the minimization of the number of flights assigned to remote terminals and the minimization of passengers’ total walking distance. The main aim of this research is to find a novel methodology to solve the FGAP. In this paper, we propose a hybrid approach called Biogeography-based Bee Colony Optimization (B-BCO). This approach is obtained by properly combining two metaheuristics: biogeography-based (BBO) and bee colony optimization (BCO) algorithms. The proposed B-BCO model integrates the BBO migration operator into to bee’s search behavior. The obtained results show the better performances of the proposed approach in ...

2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2020

Real-time information and software support systems are crucial points for performing efficient lo... more Real-time information and software support systems are crucial points for performing efficient logistics operations. Recently, most of the logistics companies have been using green-logistics solutions that encourage the use of eco-friendly vehicles, especially cargo bikes. However, for evaluating logistics' business performance, driver's exposure to emissions has often been neglected. Therefore, we proposed a Decision Support System (DSS) that considers, on the one hand, the efficiency of logistics performance and, on the other, the possibility of e-cargo bike drivers to choose the optimal route path considering two options, such as minimum travel time and minimum emission exposure. We applied the proposed DSS in a numerical application that evaluates the customer's assignment to an e-cargo bike according to the hourly traffic flows and emissions. We developed a dynamic algorithm that evaluates the path choice comparison between two route options. The choice of the minim...

IET Intelligent Transport Systems, 2018

Recently, several prominent logistic companies in Europe and the USA are seriously considering th... more Recently, several prominent logistic companies in Europe and the USA are seriously considering the idea of using drones launched from trucks and working in parallel to deliver packages. In the relevant literature, a novel problem formulation called travelling salesman problem with drone has been introduced, and some modelling and solution approaches have been presented. Existing approaches are based on the main assumption that the truck can dispatch and pick up a drone only at a node, i.e. the depot or a customer location. Here, the authors present a novel approach aimed to maximise the drone usage in parcel delivering. The authors consider that a truck can deliver and pick a drone up not only at a node but also along a route arc (en route). In this way, the operations of a drone are not strictly related to the customers' position, but it can serve a wider area along the route. The authors tested the proposed heuristic on benchmark instances and analysed the benefits introduced with the en route approach.

Transportation Research Procedia, 2018

Selection and peer-review under responsibility of the scientific committee of the EURO Mini Confe... more Selection and peer-review under responsibility of the scientific committee of the EURO Mini Conference on "Advances in Freight Transportation and Logistics" (emc-ftl2018).

PROMET - Traffic&Transportation, 2018

For a long time, many researchers have investigated the continuous network design problem (CNDP) ... more For a long time, many researchers have investigated the continuous network design problem (CNDP) to distribute equitably additional capacity between selected links in a road network, to overcome traffic congestion in urban roads. In addition, CNDP plays a critical role for local authorities in tackling traffic congestion with a limited budget. Due to the mutual interaction between road users and local authorities, CNDP is usually solved using the bilevel modeling technique. The upper level seeks to find the optimal capacity enhancements of selected links, while the lower level is used to solve the traffic assignment problem. In this study, we introduced the enhanced differential evolution algorithm based on multiple improvement strategies (EDEMIS) for solving CNDP. We applied EDEMIS first to a hypothetical network to show its ability in finding the global optimum solution, at least in a small network. Then, we used a 16-link network to reveal the capability of EDEMIS especially in t...

Transportation Research Part C: Emerging Technologies, 2017

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of... more In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers' total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.

Transportation Research Part C: Emerging Technologies, 2017

In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' ... more In this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers' dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users' changing perception of travel time also based on current network conditions. Drivers' choice models are often developed and calibrated by using Stated Preference (SP) surveys, amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experiment.