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.

Supplier Selection for Global Service Providers: a Decision Support System / Bruck, Bruno; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele; Vezzali, Dario. - (2024). (Intervento presentato al convegno 8th AIROYoung WORKSHOP tenutosi a Rende, Italia nel 14-16/02/2024).

Supplier Selection for Global Service Providers: a Decision Support System

Bruno Bruck;Manuel Iori;Carlo Alberto Magni;Daniele Pretolani;Dario Vezzali
2024

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
8th AIROYoung WORKSHOP
Rende, Italia
14-16/02/2024
Bruck, Bruno; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele; Vezzali, Dario
Supplier Selection for Global Service Providers: a Decision Support System / Bruck, Bruno; Iori, Manuel; Magni, Carlo Alberto; Pretolani, Daniele; Vezzali, Dario. - (2024). (Intervento presentato al convegno 8th AIROYoung WORKSHOP tenutosi a Rende, Italia nel 14-16/02/2024).
File in questo prodotto:
File Dimensione Formato  
VEZZALI_DARIO_8AYW.pdf

Open access

Tipologia: Abstract
Dimensione 101.76 kB
Formato Adobe PDF
101.76 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1346666
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact