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Development of a dynamic optimization framework for waste management systems

Abdallah, Mohamed, Hamdan, Sadeque, Shabib, Ahmad (2021) Development of a dynamic optimization framework for waste management systems. MethodsX, 8 . Article Number 101203. E-ISSN 2215-0161. (doi:10.1016/j.mex.2020.101203) (KAR id:90707)

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Waste to energy (WTE) technologies have emerged as an alternative solution to municipal solid waste management. WTE systems provide major environmental and economic benefits by converting waste into accessible energy, as part of an integrated solid waste management (ISWM) strategy. However, previous studies showed that establishing an ISWM strategy based on a single type of WTE systems does not necessarily realize maximum benefits. Hence, optimizing the selection of WTE systems as part of a hybrid waste management strategy can potentially achieve maximum benefits and minimize negative impacts. However, such task is challenging due to the various alternatives and objectives, particularly those related to the material and energy recovery systems. This article presents the methods used to develop a systematic optimization framework that identifies the most beneficial set of ISWM systems through mathematical modelling. The methods include the procedures of the established framework, including base model computations, as well as the comprehensive modelling and optimization methods. • The energy recovery, carbon footprint, and financial profitability are computed for selected WTE facilities. • The multi-objective mathematical programming is solved using the weighted comprehensive criterion method (WCCM). • The model is implemented in CPLEX software using mathematical programming language (OPL). © 2021 The Authors

Item Type: Article
DOI/Identification number: 10.1016/j.mex.2020.101203
Uncontrolled keywords: article; carbon footprint; computer language; energy recovery; feasibility study; human; human experiment; multiobjective optimization; municipal solid waste; software; waste-to-energy plant
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Sadeque Hamdan
Date Deposited: 09 Nov 2021 15:00 UTC
Last Modified: 09 Dec 2022 08:08 UTC
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