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DARIO VEZZALI
Assegnista di ricerca
Dipartimento di Scienze e Metodi dell'Ingegneria
Docente a contratto
Dipartimento di Economia "Marco Biagi"
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Pubblicazioni
2024
- Integrated optimization and decision support systems for attended home delivery and service problems
[Articolo su rivista]
Vezzali, Dario
abstract
2024
- Solution of a practical Vehicle Routing Problem for monitoring Water Distribution Networks
[Abstract in Atti di Convegno]
Atefi, Reza; Iori, Manuel; Salari, Majid; Vezzali, Dario
abstract
In this work, we introduce a generalization of the Vehicle Routing Problem for a specific application in the monitoring of a Water Distribution Network (WDN). In this problem, multiple technicians must visit a sequence of nodes in the WDN and perform a series of tests to check the quality of water. Some special nodes (i.e., wells) require technicians to first collect a key from a key center. The key must then be returned to the same key center after the test has been performed, thus introducing precedence constraints and multiple visits in the routes. To solve the problem, a Mixed Integer Linear Programming model and an Iterated Local Search have been implemented. The efficiency of the proposed methods is demonstrated by means of extensive computational tests on randomly created and real-world instances.
2024
- Supplier Selection for Global Service Providers: a Decision Support System
[Abstract in Atti di Convegno]
Bruck, Bruno; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele; Vezzali, Dario
abstract
In this paper, we develop a decision support system (DSS) aimed at solving a real-world supplier selection problem (SSP) for a global service provider (GSP) operating in the facility management industry. The GSP provides its customers with facility management services, which are subcontracted to external suppliers selected on the basis of multiple criteria, like economic soundness, quality of service, capacity, and closeness. The SSP is formulated as a multi-objective generalized assignment problem, where the quality and the closeness of the selected suppliers are maximized, whereas a penalty produced by overcapacity assignments is minimized. The quality of each supplier is computed by applying a weighted sum method, resulting from a multi criteria decision analysis in which the criteria weights are determined through an Analytic Hierarchy Process. The DSS is developed using a modular architecture with a relational database, a supplier evaluator, and a simulator, as well as an additional user-friendly interface. The simulator relies on a rolling horizon algorithm and three alternative configurations to assign contracts to suppliers. The effectiveness of the DSS is assessed by means of extensive computational experiments on historical data from the GSP. The results show a significant average improvement of at least 25% in terms of objective function value compared to the solution adopted by the company and prove the advantage of using the DSS.
2024
- Supplier selection for global service providers: a decision support system
[Articolo su rivista]
Bruck, Bruno; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele; Vezzali, Dario
abstract
In this paper, we develop a decision support system (DSS) aimed at solving a real-world supplier selection problem (SSP) for a global service provider (GSP) operating in the facility management (FM) industry. The GSP provides its customers with FM services, which are subcontracted to external suppliers selected on the basis of multiple criteria, like economic soundness, quality of service, capacity, and closeness. The SSP is formulated as a multi-objective generalized assignment problem, where the quality and the closeness of the selected suppliers are maximized, whereas a penalty produced by overcapacity assignments is minimized. The quality of each supplier is computed by applying a weighted sum method, resulting from a multi-criteria decision analysis in which the criteria weights are determined through an Analytic Hierarchy Process. The DSS is developed using a modular architecture with a relational database, a supplier evaluator, and a simulator, as well as an additional user-friendly interface. The simulator relies on a rolling horizon algorithm and three alternative configurations to assign contracts to suppliers. The effectiveness of the DSS is assessed by means of extensive computational experiments on historical data. The results show a significant average improvement of 25% compared to the solution adopted by the company.
2023
- A Survey of Attended Home Delivery and Service Problems with a Focus on Applications
[Abstract in Atti di Convegno]
Vezzali, Dario; Cordeau, Jean-François; Iori, Manuel
abstract
The research field on Attended Home Delivery (AHD) and Attended Home Service (AHS) problems has experienced fast growing interest in the last two decades, with the rapid diffusion of online platforms and e-commerce transactions. The COVID-19 pandemic has just fostered that interest, raising further challenges, opportunities and shortcomings that have to be tackled to answer the need for innovative methodologies as well as new policy actions. The aim of this work is to provide an extensive literature review on the state of the art for AHD and AHS problems, with a particular focus on real-world applications. A discussion of promising future research directions is also provided.
2023
- A survey of attended home delivery and service problems with a focus on applications
[Articolo su rivista]
Cordeau, Jean-François; Iori, Manuel; Vezzali, Dario
abstract
The research field of Attended Home Delivery (AHD) and Attended Home Service (AHS) problems has experienced fast growing interest in the last two decades, with the rapid growth of online platforms and e-commerce transactions. The COVID-19 pandemic has reinforced that interest, raising further challenges and opportunities that have to be tackled by innovative methodologies and policies. The aim of this work is to provide an extensive literature review on the state of the art for AHD and AHS problems, with a particular focus on real-world applications. A discussion of promising future research directions is also provided.
2023
- Solution of a practical Vehicle Routing Problem for monitoring Water Distribution Networks
[Articolo su rivista]
Atefi, Reza; Iori, Manuel; Salari, Majid; Vezzali, Dario
abstract
In this work, we introduce a generalisation of the Vehicle Routing Problem for a specific application in the monitoring of a Water Distribution Network (WDN). In this problem, multiple technicians must visit a sequence of nodes in the WDN and perform a series of tests to check the quality of water. Some special nodes (i.e., wells) require technicians to first collect a key from a key centre. The key must then be returned to the same key centre after the test has been performed, thus introducing precedence constraints and multiple visits in the routes. To solve the problem, a Mixed Integer Linear Programming model and an Iterated Local Search have been implemented. The efficiency of the proposed methods is demonstrated by means of extensive computational tests on randomly created and real-world instances.
2021
- A Decision Support System for Attended Home Services
[Abstract in Atti di Convegno]
PETRATO BRUCK, Bruno; Castegini, Filippo; Cordeau, Jean-François; Iori, Manuel; Poncemi, Tommaso; Vezzali, Dario
abstract
This Talk presents a decision support system (DSS) developed to solve a practical attended home services problem faced by Iren Group, an Italian multiutility company operating in the distribution of electricity, gas, and water. The company operates in several regions across Italy and aims to optimize the organizational system appointed to dispatch technicians to customer locations, where they perform installations, closures, or maintenance activities within time slots chosen by the customers. Indeed, attended home services (AHS) are service delivery systems in which a supplying company and a customer agree on a time window during which the customer will be home and the service will be performed. Typically, the optimization of AHS requires solving a two-stage problem, combining appointment scheduling and vehicle routing.
The DSS uses historical data and helps operations managers in performing a number of strategic decisions: grouping municipalities into clusters; designing sets of model-weeks (i.e., matrices of resources distributed among five working days and eight daily time slots of one hour, that define the capacity allocated to a given cluster); evaluating the obtained solutions by means of a dynamic rolling horizon simulator; and providing as output several key performance indicators, as well as visual optimized technician routing plans used to analyze different scenarios. The system integrates simple machine learning techniques, mathematical models, heuristic algorithms and simulation methods that have been specifically developed to take into account different quality of service levels, in accordance with the directives imposed by the authority that regulates the Italian market.
Computational experiments carried out on data provided by the company confirm the efficiency of the proposed methods, both in terms of effort reduction and routing costs saving (10% on average) [4]. Additionally, the DSS constitutes a powerful tool that can support the company in the strategical evaluation of existing and potential market opportunities.
2021
- A Decision Support System to Evaluate Suppliers in the Context of Global Service Providers
[Relazione in Atti di Convegno]
Bruck, Bruno Petrato; Vezzali, Dario; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele
abstract
In this paper, we present a decision support system (DSS) developed for a global service provider (GSP), which solves a real-world supplier selection problem. The GSP operates in the Italian market of facility management, supplying customers with a variety of services. These services are subcontracted to external qualified suppliers spread all over Italy and chosen on the basis of several criteria, such as service quality, availability and proximity. Selecting the best supplier is a complex task due to the large number of suppliers and the great variety of facility management services offered by the GSP. In the proposed DSS, the choice of the best supplier for a certain service is made according to a thorough multi-criteria analysis. The weights for the criteria were generated by implementing both a simplified analytic hierarchy process and a revised Simos' procedure, later validated by the decision makers at the GSP. The DSS provides quick access to historical performance data, visual tools to aid decisions, and a suggested ranked list of suppliers for each given contract. The effectiveness of the proposed system was assessed by means of extensive simulations on a seven-year period of real-data and several rounds of validation with the company.
2021
- Smart-Meter Installation Scheduling in the Context of Water Distribution
[Abstract in Atti di Convegno]
Baschieri, Davide; Iori, Manuel; Magni, Carlo Alberto; Marchioni, Andrea; Vezzali, Dario
abstract
In this work, we propose a Mixed Integer Linear Programming (MILP) formulation to model a Smart-Meter Installation Scheduling Problem (SMISP) in the context of water distribution. The model has been used to solve a real case study from a multi-utility company operating in the Italian market. Specifically, in compliance with the European and the Italian regulations on metering, a distribution company is obligated to periodically control meters and substitute them in case they have reached their lifespan. In the examined case study, the multi-utility company has opted for a massive substitution plan in order to install innovative “walk-by smart-meters” in place of traditional mechanical meters.
The MILP formulation aims at integrating both the operational and the financial perspective of the SMISP. In particular, the objective function has been carefully defined in order to maximize the Net Present Value (NPV) of the massive substitution plan, including the operational savings produced by using the walk-by smart-meters, the additional incomes originating from the gradual charge of substitution costs on customers’ invoices as considered by the Italian Authority, the depreciation of walk-by smart-meters, the investment costs, and the impact of income taxes on the objective function. The final goal of the proposed formulation is to define a scheduling for the massive substitution plan that satisfies a number of operational constraints and produces the maximum NPV.
2020
- A Decision Support System for Attended Home Services
[Articolo su rivista]
Bruck, Bruno P.; Castegini, Filippo; Cordeau, Jean-François; Iori, Manuel; Poncemi, Tommaso; Vezzali, Dario
abstract
This paper describes a decision support system developed to solve a practical attended home services problem faced by Iren Group, an Italian multiutility company operating in the distribution of electricity, gas, and water. The company operates in several regions across Italy and aims to optimize the dispatching of technicians to customer lo- cations where they perform installations, closures, or maintenance activities within time slots chosen by the customers. The system uses historical data and helps operations managers in performing a number of strategic decisions: grouping municipalities into clusters; designing sets of model-weeks for each cluster; evaluating the obtained solutions by means of a dynamic rolling horizon simulator; and providing as output several key performance indicators, as well as visual optimized technician routing plans to analyze different scenarios. The system uses mathematical models and heuristic algorithms that have been specifically developed to take into account different service levels. Computational experiments carried out on data provided by the company confirm the efficiency of the proposed methods. These methods also constitute a powerful tool that can be used by the company not only to reduce costs but also to help them in their strategic evaluation of existing and potential market opportunities.
2019
- A Decision Support System to Evaluate Suppliers in the Context of Global Service Providers
[Abstract in Atti di Convegno]
Bruck, Bruno Petrato; Iori, Manuel; Pretolani, Daniele; Vezzali, Dario
abstract
In this work, we propose a decision support system (DSS) to evaluate a set of suppliers by considering a multiplicity of variables. The DSS has been implemented to solve a real problem faced by a Global Service Provider (GSP) operating in the Italian market, and is based on a simplified Analytic Hierarchy Process (AHP) application.
GSPs operate in the field of facility management, providing customers with general maintenance services for their real estate assets. To realize this purpose, they subcontract to selected suppliers the execution of services. A comprehensive and multi-criteria evaluation of suppliers is the key element to select the most fitting one for a specific service requested by a particular customer. This process of suppliers’ selection directly affects success and duration of the relationship between the GSP and its customers.
The content of our work consists of five parts: first, variables identification and description, necessary to create an objective and comprehensive evaluation of GSP’s suppliers; second, weights calculation of defined variables accordingly to the AHP method; third, mathematical model formulation in order to precisely describe the decision problem; fourth, data collection and database creation containing all of the raw data necessary to perform the evaluation; fifth, DSS development and test with potential users through a web application prototype specifically developed for the problem.