Reverse logistic network optimization in the CRD industry: the case of wood
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School of Business |
Master's thesis
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Date
2024
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Mcode
Degree programme
Business analytics
Language
en
Pages
63
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Abstract
This thesis addresses the increasing need for more sustainable supply chain practices in the construction, renovation, and demolition (CRD) industry with a focus on reverse logistics for wood waste. While the CRD industry acts as one of the largest global waste producers, and wood waste constitutes a significant fraction by volume, research on optimising reverse logistics networks (RLNs) for the CRD industry remains limited, and especially wood waste remains limited. This study aims to fill the research gap by building on the foundational work of Trochu et al. (2018), adapting and extending their mixed-integer linear programming (MILP) model to a densely populated and highly regulated environment where landfilling is no longer the default option. Moreover, sustainability-orientated initiatives, such as on-site mobile processing, are becoming increasingly prevalent. The model's revisions encompass the design of transfer stations that also function as sorting facilities, the integration of mobile processing units at key CRD locations for initial sorting, and the establishment of treatment facilities for contaminated wood. These modifications offer a more precise representation of London's operating dynamics and regulatory framework. This research also employs scenario-based analysis in the case study of Greater London, UK. A total of 27 scenarios is utilised to replicate the real-world complexity and examine the impacts of uncertainties regarding the source location, quantity, and quality on the RLNs. The results indicate that strategic capacity enhancements at transfer stations can create a significantly larger buffer zone under supply uncertainties. Hence, transportation expenses, reliance on landfills, and total network costs can be minimised. For instance, compared to the baseline scenario depicting the current Greater London RLN, an optimised RLN configuration diminishes landfilling from 721,453 to 242,893 tonnes, enhances recycled material flow by 50%, and decreases overall costs by 7.5%. Transportation cost remains a major cost parameter, even in the case of reduced distance between nodes within the densely populated region. This thesis contributes to the literature by offering insights into RLN design among many uncertainties, thereby encouraging decision-makers to invest in flexible capacity planning and quality-improvement measures during the collection phase. The results suggest that policymakers and industry stakeholders ought to advocate for more sustainable, cost- efficient, and effective wood waste management through the reconfiguration of networks and the provision of supportive economic incentives.Description
Thesis advisor
Peura, HeikkiKeywords
reverse logistics network, network optimization, wood waste recycling, mixed-integer linear programming, construction, renovation, and demolition (CRD) waste, supply location, quality, and quantity uncertaintie