Showing papers presented at "International Conference on Service Operations and Logistics, and Informatics in 2017"

Internet of vehicles: Cloud and fog computing approaches

Abstract: Some of the mobility challenges in the cities can be approached with the Internet of Things, Cloud Computing, and Fog Computing. In this work we consider the city as a system of systems and focus on the interaction of those entities with the mobility systems. A key element that allows this interaction is a vehicle on-board unit. In this work we address the interconnection, enabling technologies, interoperability, scalability, geo-distribution and time constrains aspects in the architectural design of mobility systems. For this we propose the On-Board Unit architecture and cover three different levels of technification in information and communication technologies. Based on this differentiation we are able to include Cloud and Fog Computing into our proposed designs.

A novel deployment of smart Cold Chain system using 2G-RFID-Sys temperature monitoring in medicine Cold Chain based on Internet of Things

Abstract: Temperature monitoring of medicines is essential for product quality and patient safety. Product quality is influenced by temperature perturbations and time delays in interventions. Thanks to Internet of Things (IoT) considerable progress has been made in recent years in the improvement of temperature monitoring devices. However, temperature monitoring in medicine Cold Chain remains challenging. In this paper it is presented a conceptual model aiming at overcoming challenges of medicine Cold Chain related to temperature monitoring. The major particularity of our model is that it considers the complete Cold Chain according to two perspectives of pharmaceutical and healthcare industries in a single study. Besides this model can be applied also in vaccine Cold Chain and in temperature-controlled logistics of laboratory medicine. Our conceptual model supports the development of a smart Cold Chain system for temperature monitoring based on IoT. Our smart Cold Chain system can be used to improve Cold Chain responsiveness by studying weaknesses and deciding what Cold Chain characteristics to improve.

Externalities reduction strategies in last mile logistics: A review

Abstract: In this paper a review of recent contributions in scientific literature on the last mile logistics is presented. The increase in freight transport and the actual growing trends are responsible, in the urban areas, of a critical increase of congestion, air pollution, noise and others externalities that involve the major cities in the world. New technologies and organizational strategies allow handling in a more efficient way the last mile delivery in urban areas. Papers that contribute significantly and with original proposal in reducing externalities in urban logistics are analysed in this work.

Actors interactions and needs in the European electromobility network

Abstract: The standardization of services in the European electromobility network is becoming one of the main goal of researchers and practitioners. In this context, the objective of the paper is proposing a general view of the main needs and functions of the involved actors and stakeholders, and to state their interactions within the electromobility network. In particular, actors and stakeholders are grouped in so called macro-areas, and the interoperability and cooperation at both macro-areas and actors levels are provided by means of Unified Modeling Language (UML) diagrams.

An information system for masonry building monitoring

Abstract: The large-scale management and monitoring of ancient buildings, in particular of churches, is a complex issue for the heritage buildings holders. The scientific and technical communities study new methods to improve these operations through Information and Communication Technology tools. This paper proposes the first steps of an innovative methodological approach to develop an information system that allows the monitoring of many masonry churches using limited resources. The information system consists of a computer platform (named Quality Detection Platform — QDP) and a mobile device application dedicated to the acquisition of large-scale data through Internet of Things (IoT) support. This tool allows recording and reporting structural problems through photographic surveys and additional information provided by the smart devices positioned on the structure: a set of Bluetooth Smart sensors positioned on specific building components. The data collected are processed by the QDP that studies and classifies the critical issues. In order to assess the proposed methodology, the case study of the church “SS. Salvatore” in Bari (Italy) is developed.

A decentralized control strategy for optimal charging of electric vehicle fleets with congestion management

Abstract: This paper proposes a novel decentralized control strategy for the optimal charging of a large-scale fleet of Electric Vehicles (EVs). The scheduling problem aims at ensuring a cost-optimal profile of the aggregated energy demand and at satisfying the resource constraints depending both on power grid components capacity and EV locations in the distribution network. The resulting optimization problem is formulated as a quadratic programming problem with a coupling of decision variables both in the objective function and in the inequality constraints. The solution approach relies on a decentralized optimization algorithm that is based on a variant of ADMM (Alternating Direction Method of Multipliers), adapted to take into account the inequality constraints and the non-separated objective function. A simulated case study demonstrates that the approach allows achieving both the overall fleet and individual EV goals, while complying with the power grid congestion limits.

Smart parking management in a smart city: Costs and benefits

Abstract: Today cities are responsible for more than 75% of waste production, 80% of emissions, and 75% of energy utilization. With regard to Europe, road transportation produces about 20% of the total CO2 emissions, out of which 40% is generated by urban mobility. It is estimated that vehicles cruising for free parking spaces cause 30% of the daily traffic congestion in an urban downtown area. In this article we attempt to show, through a simulation and an assessment model, how ITS may impact on urban parking management considering both people and freight transportation, and quantified the economic and social benefits which can be obtained. Although some benefits have been already examined by previous authors (e.g. in terms of reduction of time spent in searching a free parking spot), there is still a general lack of quantitative models able to assess the impacts of ITS technologies for urban parking. In this regard, one distinctive contribution of this article is that it combines people and freight transportation modes in a single model. First, we developed a model in order to simulate the urban parking system before and after the adoption of the Smart Parking solution. The output of the simulation model consists in the percentage reduction of the time spent by drivers of cars and vans in searching a free parking spot. Then, this percentage has been used to assess the economic and social benefits of a Smart Parking application in the City of Milan (Italy), in which the “pay and display” parking spots are provided with sensors able to communicate if the space is free or not. The analysis considers two perspectives: on the one hand the parking operator company, which can increase its revenue due to the reduction of people that do not pay for parking. On the other hand, the city-users (i.e. citizens, tourists, off-site students, etc.), who can reduce the time spent for searching a free parking spot, thus reducing fuel consumption and CO 2 emissions. The results obtained showed that these technologies would help each driver to save an average of 77.2 hours every year, 86.5 euros in fuel costs, and the entire city of Milan could reduce CO2 emissions by 44,470 tons per year (out of a total of 4,144,000 tons annually produced by road traffic in the area of Milan). In addition, these technologies help the parking operator company in improving the total revenue of around 9 million euros per year. If considering the required costs to implement the Smart Parking solution, the Discounted Payback Period for the parking operator is lower than 2 years.

IoT system for anytime/anywhere monitoring and control of vehicles' parameters

Abstract: This paper presents an IoT (Internet of Things) system designed to allow the monitoring and control of parameters of the users' vehicles, anytime and anywhere in the world, through the Internet. The system prototype was developed and tested using an electric vehicle (EV) and the respective sensor systems. The main components of the proposed IoT system are: a Bluetooth Low Energy (BLE) intra-vehicular wireless sensor network (IVWSN); a mobile device that acts both as the vehicle's gateway, connecting the IVWSN to the Internet, and as the vehicle's human machine interface (HMI); an online server/database, based on Firebase; a client, which can be either a mobile device or a personal computer; and a residential wireless sensor network (WSN). The use of a wireless network to collect sensor data inside of the vehicle introduces some advantages when compared with conventional wired networks, whereas the inclusion of a residential WSNs in the proposed IoT architecture allows the provision of additional features, such as automatic control of the EV battery charging process. Experimental results are provided to assess the performance of the developed IVWSN and HMI.

A multi-objective formulation for multimodal transportation network's planning problems

Abstract: Multimodal transport offers an advanced platform for more efficient, reliable, flexible and sustainable freight transport. In order to achieve sustainable planning in a complicated transport system, it is very interesting to use methods include in the fields of operational research. In this article, we propose a mathematical model to solve the multi-objective optimization problem applied in the multimodal transport network. In this paper, we will start with a brief description of the existing literature works that interested in the optimization problem as well as the planning of the multimodal transport network. The goal of this study will be helping to propose an efficient mathematical model. Indeed, the main proposal of the article is a multi-objective programming model with linear and nonlinear constraints. Computational experiments are carried out to test the effectiveness of the proposed model, which has been proved by a comparison with the literature model.

Optimal fuel consumption for heavy trucks: A review

Abstract: This paper deals with the problem of reducing fuel consumption and pollutant emissions of Heavy Duty Vehicles (HDV). The overall objective of improving the efficiency of the HDV can be obtained by employing the most advanced technologies in powertrain control and intelligent transportation systems, by taking into account road topography, traffic, weather conditions and driver behavior. This paper presents a review of the recent researches on the technologies to reduce fuel consumption and pollutant emissions for HDV. In particular, the reviewed research contributions are presented in four main areas: driver behaviour, road density evaluation, route planning and speed control.

Omni-channel service operations: Building technology-based business networks

Abstract: This article investigates how omni-channel services operations are building technology-based business networks. It uses a case study research, which includes multiple sources of data collection for triangulation purposes, to study a real-life phenomenon. The results suggest that omni-channel companies are changing their landscape to business networks, looking for competitive advantages over their rivals. But this move incorporates new challenges, as it requires a transition based on operations management to allow these firms to adapt their processes and channels, in order to be able to collaborate in a heterogeneous network of firms. Another possible solution is the integration of innovation technologies that are enabling the combination of firm capabilities to underpin collaborative relationships. Previous research also suggests that service operations management in an omni-channel services context is largely unaddressed, as this discipline is essential for the edification of technology-based business networks. Thereby, this article provides real-life statements and examples of firms that are moving their service operations into a business network paradigm. Subsequently, since omni-channel services are multidisciplinary in nature, these exploratory results represent a fruitful opportunity for future research to involve other disciplines than service operations.

Post-production analysis approach for drone delivery fleet

Abstract: This paper treats a drone delivery parcel's problematic in an urban area. The civil application of drone has been developed during these last decades especially drone delivery applications. In this paper, we focus on drone delivery application in the urban area for last-mile parcel delivery. The new issue is not only the drone design but also the logistics support of a massive fleet of drones with a mission to deliver parcels in a dense urban area. We hereby treat problematic by focusing on Logistics Support System. In this context, the commercialized drone is a considered as a system on the shelf. we propose a Post-Production Logistics Support Analysis to cover the exploitation phase of a drone delivery operator.

SMART sensor network: With Bluetooth low energy and CAN-BUS

Abstract: This paper proposes a system to monitor, through the internet, the data of a logistics distribution truck. For this, it was implemented a reliable and flexible wireless sensor network with low energy consumption. The technology used for the radio system was Bluetooth Low Energy (BLE). Each node in the network contains one type of sensor. The sensors information together with GPS and On-Board Diagnostics (OBD) data collected by the central unit, and later transmitted to the cloud by GSM or Wi-Fi.

Logistics in omni-channel retailing: Modelling and analysis of three distribution configurations

Abstract: The growing importance of the online channel and the increased deployment of new technologies such as smart mobile devices and social networks create new opportunities and challenges for traditional retailers. The retailing industry is moving to a new phase, in which the distinctions between traditional and online channels disappear, namely omni-channel (OC) retailing. The new challenge is to understand how multiple channels can be synergistically managed to provide a seamless customer experience. In OC retailing, logistics represents a key success factor due to its impact on both customer service and total costs. Retailers need to define the distribution configuration for serving the online demand, making decisions on the integration level between online and traditional channels. Companies can set an ad hoc network for the online channel, or use the same network for both online and traditional channels at warehouse and/or transport levels. In this paper, we developed an assessment model of the operational costs for three distribution configurations in OC retailing. The model was also applied to a real Italian case operating in the consumer electronics industry. Results highlighted that the search for synergies between online and traditional flows in both warehouse and transport activities is important for the economic sustainability of OC systems.

Online scheduling of a fleet of autonomous vehicles using agent-based procurement auctions

Abstract: We propose a novel distributed approach for the problem of scheduling a fleet of autonomous vehicles. Our distributed system avoids a single point of failure, is scalable, fault tolerant and robust. We describe an agent-based distributed system to conduct a set of procurement auctions. The vehicles are the “sellers” and the passengers are the “buyers” in the auction. Each vehicle bids for the passengers with a bid value which is an inverse function of the time it would take the vehicle to reach the passenger. In our agent based architecture, the various software agents reside on different systems and we describe distributed algorithms for their communication. We have performed simulations of a vehicle fleet in two different locations (Bangalore, India and Tyson's Corner, Virginia, USA) and compare the maximum and average waiting times of the passenger of our algorithm with a FIFO algorithm. We also compute the ratio of the time in which the vehicle is servicing a passenger to the total time to compute the fuel wastage. The results show that our system improves the maximum and average waiting times of the passengers, as well as the fuel costs for the vehicle fleet. Furthermore, we show that such a distributed system reduces the time it would take on average to respond to customer requests, as compared to a system which is not distributed.

A flexible platform for intermodal transportation and integrated logistics

Abstract: This paper proposes an application of Information and Communications Technology (ICT) tools and Internet of Things to support intermodal transport and integrated logistics. In particular, the design and development of a new ICT platform is presented in order to facilitate the connectivity of the logistics systems, applications or objects from stakeholders to any logistics collaborative environment. The proposed platform aims to i) provide technological solutions to enhance and simplify collaboration among actors along the supply chain; ii) adopt and provide core functionalities to improve, optimise and automate transport and logistics operations within supply collaborations; iii) simplify information exchange within an integrated security framework. Finally, we show a case study in order to enlighten the effectiveness of the proposed ICT platform.

Acceleration strategies of the column generation method for the crew scheduling problem

Abstract: Crew scheduling is an important optimization problem in the railway industry. In last decades, the extension of computational resources made it feasible to address real-life problems generating large-scale set covering problems. Broadly used is the concept of shift frames, which is well suited current practice of several railway operators. In the case when the problem is described by one complete model, which covers all characteristics of the crew scheduling problem, it may lead to a large linear programming problem formulation, which can attack the limits of a common IP-solver. To overcome this obstacle, column generation technique can be used. Column generation technique can reduce the size of solved model. Despite the fact that it cannot find the optimal solution, it can enable to solve larger instances. In this contribution we explain the concept of frames used in design of periodic timetable and analyze the property of the particular frame networks. We explain the column generating principle in connection with the crew scheduling problem. We present improving methods to accelerate the column generation method that are able to find solution of the solved sub-problem faster and different strategies of producing the initial collections of columns, which enable to make the column generation process more effective. Although the computational time in the scheduling problems is not an critical issue, the reduce of the computational time can enable to use this method in the decision supporting tool for the crew schedule design under practical conditions, especially in large scale problems. To test proposed improvements we use various benchmarks of real problems from crew scheduling in railway transportation systems.

Investment evaluation in seaports for increasing the rail split modality in multimodal freight networks

Abstract: This paper concerns an analysis aimed at choosing the best investments in seaports for improving the rail split modality when transferring goods from ports to final destinations. Starting from a current network infrastructure, already optimized according to previous studies, we show that it is possible to obtain a new rail capacity able to increase the modal split thanks to possible alternative investments. First, a Mixed Integer Linear Programming (MILP) model is proposed; then, a set of possible financial interventions is examined in such a way to obtain a desired rail share for the import-containerized flows. The objective function of the proposed model aims at minimizing the costs of the adopted investments and the overall logistic costs, given by transportation, facility and external components. Externalities include pollutant, noise and congestion factors. The logistic networks originated from the Ligurian ports (Italy) is the test bed of the present research work.

A pre-process clustering methods for the waste collection problem

Abstract: Modern cities produce larger amounts of waste causing profound negative impacts on our natural environment. For this reason, processes related to waste collection, transportation, transformation and final disposal have increased their importance and major adequacy is desirable. Several Waste Management (WM) problems have to be solved in order to obtain efficient related services. Traditional Vehicle Routing Problem and Waste Collection Problem solution approaches presented in the literature are not suitable to face problems related to specific topology of the city, districts, street dimension and shape of the clusters. In this paper we propose a pre-process cluster solution in order to take into account different information such as street names, street dimension and civic number in order to create cluster more acceptable by the final users. In order to show the effectiveness of the proposed methodology, we compare hierarchical and spectral clustering-based algorithms. Finally, we apply our proposal in a real case study based on a data set extracted from a city in the north-east of Italy.

Genetic algorithms hybridized with the self controlling dominance to solve a multi-objective resource constraint project scheduling problem

Abstract: The Resource Constraint Project Scheduling Problem (RCPSP) is one of the most challenged scheduling topics. Compared to the other scheduling problems, the RCPSP pays special attention to the consumable resources with limited capacities, which is the major issue that industry has to cope with. In our study, we tackle a Multi-Objective RCPSP with minimization of the makespan, the total job tardiness and maximization of the workload balance level. Non-dominated Sorting Genetic Algorithm II (NSGAII) and NSGAIII are applied at first to find approximated Pareto fronts. In particular circumstances, decision makers would prefer preselected propositions than the whole Pareto front. For this reason, we have integrated in our study, the Self Controlling Dominance Area of Solutions (SCDAS) in our algorithms find more fine-grained Pareto fronts, and solutions with good qualities on all objectives. Small, medium and large size instances, featured by different parameters of jobs and resources are tested. A comparative study is carried out where the hypervolume and the metric-C are used to evaluate the performances of different methods. The improvements brought by the SCDAS are proved regarding both metrics.

A method for estimating annual cost reduction of IT service deals

Abstract: Highly valued Information technology (IT) service contracts involve the delivery of complex IT services, such as migrating the client's IT infrastructure to the Cloud, Mainframes, among others. IT service providers usually compete to win these IT service contracts. In order to bid on such deals, IT service providers need to price/quote the solution that they propose to the client, trying to convince him to use their services. A few analytical methods in the literature have been provided for pricing these deals. However, these methods ignore an important characteristic of these services; that is they are typically characterized by a decreasing cost profile in subsequent years to the first year. Typically, these methods require solutioners to manually input these annual cost reductions. In this paper, we present an analytical way for calculating this cost reduction, if applicable, via mining historical data. We show that using our methodology could achieve significant increase in the accuracy of estimating the costs and prices of IT service deals.

Mobile device sensing system for urban goods distribution logistics

Abstract: This paper presents a low cost mobile application (app) integrated on an Internet of Things (IoT) ecosystem, which uses varied sensor information collected by mobile devices to track and assist on the logistics of urban goods distribution processes. The proposed approach is leveraged by the trend of decreasing costs for mobile data communication in urban environments. Taking into account basic sensor data available in mobile devices (e.g., GPS, accelerometer and magnetometer), it is possible to track the users' movements and adopted routes, identify transit times and driving styles, identify the quality of roads, and track the process of loading/unloading of urban goods. This data can also be analyzed through a data mining process to identify patterns, present driving advice and perform a resource optimization process.

The multi-shift single-vehicle routing problem under fuzzy uncertainty

Abstract: In this paper, we study the single-vehicle routing problem (VRP) with time windows, multi-shift, and fuzzy uncertainty. In this problem, one vehicle is used repeatedly to serve demand over a planning horizon of several days. The problem is inspired by a routing problem in maintenance activities, where one maintenance crew uses a vehicle to perform jobs in various locations. Crew operates in shifts and always returns to depot before shift ends (no overtime is allowed). The objective consists in completing all the maintenance jobs in various locations minimizing the number of shifts the crew is used, and reducing the shift duration time. We study the effect of uncertainty in travel and job processing time on KPI. We develop an Artificial Immune Heuristic to solve the addressed problem. A numerical real test study is performed in order to investigate the problem. We propose a framework to evaluate the uncertainty effect. Results show important time saving can be obtained with the proposed approach.

Order review and release methods in internal logistics of a MTO company

Abstract: Due to change in customer requirements, companies, especially MTO companies, started focusing on the internal flow. Therefore the study of different production planning techniques, particularly order review and release methods, in a pure flow shop is slowly becoming important. Literature shows that research so far is mostly confined in theoretical studies, but there is scarcely any evidence of applying the order review and release methods in a real time company. Therefore, the internal logistics system of a MTO company in Italy is studied. The system follows a pure flow shop configuration. After collecting the data from the company, the different parameters are determined. Two different order review and release methods, limiting, based on heuristics, and balancing, based on optimization model, are applied and compared with the current condition. The simulation results show better performance of balancing method compared to limiting method for the internal flow of the company.

Outsourcing strategies and distribution models in Italian Pharma Supply Chain

Abstract: In the pharmaceutical supply chain, all players have to ensure the highest level of service while containing costs, because of the ethical issues concerning drugs. The outsourcing of logistics should be recognized as a competitive lever, especially in this complex and highly regulated industry. Based on these premises, the research objective of this study is to investigate the relationship between the outsourcing strategies of manufacturers and the logistics services offered by Third-Party Logistics Service providers (3PLs). To achieve this objective, a multiple case study was designed to analyse the different physical distribution models adopted by pharmaceutical companies. We collected qualitative data and the subjective perceptions of several logistics directors, conducting structured interviews with 11 pharmaceutical companies and six 3PLs. We have identified three physical distribution models, on the basis of the number and location of the warehouses used (single warehouse, dual warehouse and multi-warehouse models). We discovered that there is a strict relationship between the physical distribution model adopted by pharmaceutical companies and their features (i.e. the main distribution channel, product portfolio, target service level, transport and warehousing costs and other company related issues). Our research also offers an empirical insight into the key logistic services that 3PLs should offer within the pharma industry. In conclusion, the study draws a roadmap to guide pharmaceutical companies in their strategic logistics decisions in Italy, while also considering possible future trends deriving from changes to European regulations.

Effective data curation for frequently asked questions

Abstract: Frequently-asked-question (FAQ) systems are effective in operating and reducing costs of IT services. Basically, FAQ data preparation requires data curation of available heterogeneous question-and-answer (QA) data sets and creating FAQ clusters. We identified that the labor intensiveness of data curation is a major problem and that it strongly affects the final FAQ output quality. To deal with this problem, we designed a FAQ creation system with a strong focus on the effectiveness of its data-curation component. We conducted a field study by inspecting two sources: incident reports and a QA forum. The first source of incident reports showed a high F-score of 89.9% (precision: 82.5%, recall: 100%). We also applied the same set of parameters to 300 entries of the QA forum and achieved an F-score of 94.3% (precision: 94.9%, recall: 93.8%).

Performance assessment for intermodal transportation systems: A case study

Abstract: This paper proposes a methodology to evaluate an Intermodal Transportation System (ITS). These systems are very complex and a lot of different actors are involved. The evaluation process should take into account concurrent needs and goals. Moreover, the data and the importance of different indicators are strictly related to the judgments of individual experts. Then it is necessary to have a methodology able to collect all the independent judgments and merge them in order to evaluate the whole system performances. The paper proposes a general methodology based on the Analytic Hierarchy Process to evaluate the behavior of the ITS system. Moreover, the hierarchy including the typical factors that compose a logistic system has been identified. In order to show the effectiveness of the proposed methodology, we present a real case study consisting of the port of Trieste (Italy), the intermodal terminal and the highway connecting them. Several Key Performance Indicators are evaluated to provide assessment procedure.

Optimized multi-agent routing in shared guidepath networks

Abstract: This paper overviews a research program of ours that concerns the routing of a number of traveling agents over a transportation medium that is abstracted as a “zone”-controlled guidepath network. From an application standpoint, this class of problems arise in the real-time management of the traffic that takes place in many contemporary material handling systems. But quite interestingly, the same problems also arise in the routing of the ionized atoms that are the elementary information carriers in the context of quantum computing. The paper provides a conceptual description and some motivational applications for the aforementioned problems, places these problems in the context of the existing literature, and outlines the methodological base and the key results that have been developed in the presented research; detailed expositions of these technical developments can be found in the provided references.

Information-centric publish-subscribe mechanisms for Intelligent Transportation Systems

Abstract: Emerging services for Intelligent Transport Systems put the information content at the centre of the communication process, require a seamless support of mobile users, and target a real-time and asynchronous data dissemination. The Information-Centric Networking paradigm has all the potentials to fulfill these requirements, thanks to its ability to distribute contents through publish-subscribe communication mechanism, also in mobile conditions. Unfortunately, most of publish-subscribe models proposed in the literature consider static scenarios. The work presented herein formulates two publish-subscribe schemes, based on the pull-based and push-based approaches, discusses their behavior through simplified examples, and evaluates the communication overhead they incur in realistic scenarios through computer simulations.

Evaluating different methods for determining road grade best suited to advanced bus transportation systems

Abstract: Real world fuel consumption and emission models are sensitive to road grade estimates. The developments of eco-routing and eco-driving solutions makes the development of large scale collections of road grade profiles of importance. Therefore, there is a need to collect accurate, large scale, road grade profiles. Existing intelligent transport systems (ITS) like Advanced Bus Transportation Systems (ABTS) provide an opportunity to collect large amounts of data for post processing development of road grade profiles. This paper explores different techniques for determining road grade estimates suited to ABTS. Five studies were replicated in this work and evaluated in real world experiments against the Google Elevation API.