Integrated smart waste management (ISWM) is an innovative and technologically advanced approach to managing and collecting waste. It is based on the Internet of Things (IoT) technology, a network of interconnected devices that communicate and exchange data. The data collected from IoT devices helps municipalities to optimize their waste management operations. They can use the information to schedule waste collections more efficiently and plan their routes accordingly. In this study, we consider an ISWM framework for the collection, recycling, and recovery steps to improve the performance of the waste system. Since ISWM typically involves the collaboration of various stakeholders and is affected by different sources of uncertainty, a novel multi-objective model is proposed to maximize the probabilistic profit of the network while minimizing the total travel time and transportation costs. In the proposed model, the chance-constrained programming approach is applied to deal with the profit uncertainty gained from waste recycling and recovery activities. Furthermore, some of the most proficient multi-objective meta-heuristic algorithms are applied to address the complexity of the problem. For optimal adjustment of parameter values, the Taguchi parameter design method is utilized to improve the performance of the proposed optimization algorithm. Finally, the most reliable algorithm is determined based on the Best Worst Method (BWM).

An Allocation-Routing Optimization Model for Integrated Solid Waste Management / Hashemi-Amiri, Omid; Mohammadi, Mostafa; Rahmanifar, Golman; Hajiaghaei-Keshteli, Mostafa; Fusco, Gaetano; Colombaroni, Chiara. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - (2023). [10.1016/j.eswa.2023.120364]

An Allocation-Routing Optimization Model for Integrated Solid Waste Management

Mostafa Mohammadi
Co-primo
Methodology
;
Golman Rahmanifar
Secondo
Validation
;
Gaetano Fusco
Supervision
;
Chiara Colombaroni
Supervision
2023

Abstract

Integrated smart waste management (ISWM) is an innovative and technologically advanced approach to managing and collecting waste. It is based on the Internet of Things (IoT) technology, a network of interconnected devices that communicate and exchange data. The data collected from IoT devices helps municipalities to optimize their waste management operations. They can use the information to schedule waste collections more efficiently and plan their routes accordingly. In this study, we consider an ISWM framework for the collection, recycling, and recovery steps to improve the performance of the waste system. Since ISWM typically involves the collaboration of various stakeholders and is affected by different sources of uncertainty, a novel multi-objective model is proposed to maximize the probabilistic profit of the network while minimizing the total travel time and transportation costs. In the proposed model, the chance-constrained programming approach is applied to deal with the profit uncertainty gained from waste recycling and recovery activities. Furthermore, some of the most proficient multi-objective meta-heuristic algorithms are applied to address the complexity of the problem. For optimal adjustment of parameter values, the Taguchi parameter design method is utilized to improve the performance of the proposed optimization algorithm. Finally, the most reliable algorithm is determined based on the Best Worst Method (BWM).
2023
waste management System; vehicle routing problem; waste to energy; best worst method; meta-heuristic
01 Pubblicazione su rivista::01a Articolo in rivista
An Allocation-Routing Optimization Model for Integrated Solid Waste Management / Hashemi-Amiri, Omid; Mohammadi, Mostafa; Rahmanifar, Golman; Hajiaghaei-Keshteli, Mostafa; Fusco, Gaetano; Colombaroni, Chiara. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - (2023). [10.1016/j.eswa.2023.120364]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1679157
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