Construction waste management in the context of circular economy

Abstract

Construction industry is a major consumer of raw materials and generates a large amount of construction and demolition waste (CDW), while boosting economic growth and social development. With the public awareness of sustainable development, the construction industry adopts circular economy concept to maximize resource utilization and minimize CDW. However, there are some significant challenges in CDW management, such as a lack of an integrated framework. This thesis investigates related technologies and decision-making models in CDW management in the context of circular economy using Hong Kong as an example with four scenarios. The first scenario presents a three-layer building information modeling (BIM)-based framework for CDW management. This scenario integrates advanced technologies like Internet-of-Things with BIM to collect, maintain and analyze CDW-related data for supporting building demolition activities. This framework includes three key services, i.e., scanning and surveying service, building demolition service, and waste transportation service, which are verified through case studies, to uplift demolition efficiency. Moreover, the cost-benefit analysis is employed to quantify the advantages and disadvantages of the proposed framework using the data from Hong Kong’s residential buildings. The analysis presents the cost benefits become essential even if half of the demolition waste is reused and recycled. The second scenario investigates a building demolition planning (BDP) problem which involves many negotiations between general contractors and subcontractors. An automated negotiation mechanism is proposed to streamline negotiation processes and enable multiple negotiations to be executed simultaneously, considering multiple attributes. It includes an atomic demolition service negotiation model for a specific demolition task and a composite demolition service coordination model that coordinates concurrent negotiations for a demolition project. An integer linear programming model is formulated to compare performance of the proposed negotiation mechanism. Compared to the traditional optimization model, the negotiation mechanism benefits general contractors with an improved success rate of negotiations. The third scenario focuses on a reverse logistics (RL) network design problem. A multi-objective mixed integer linear programming (MILP) model is proposed to design an RL network for multiple types of CDW considering the uncertain transportation distance, the uncertain transportation cost and the uncertain amount of CDW. A fuzzy random variable is employed to address uncertainties and an ε-constraint method is introduced to address the conflicting objectives. This scenario uses a real-life case from Hong Kong to verify the proposed model. Moreover, sensitivity analysis is conducted to explore the effect of key parameters on RL network design. The results show controlling the carbon emission limit could balance the workload of facilities. The fourth scenario formulates stylized models to investigate the pricing and remanufacturing effort decisions when a prefabricated construction supply chain (PCSC) competes with a remanufactured PCSC. One building contractor and one prefab manufacturer are considered. Given different market power structures and competition relationships, five game-theoretic models are developed to investigate their optimal decisions. Numerical studies are conducted to derive useful managerial implications for stakeholders. The results show that the supply chain members employing the remanufacturing strategy gain more profit.