This study examined logistics planning in the modular integrated construction supply chain (MiC-SC). Existing models overlook two important characteristics of the MiC-SC—the dynamic behavior of its stakeholders, and the uncertain interactions between its activities and resources—making their applicability limited in real practice. The literature also lacks an understanding of which logistics and construction decisions significantly impact the MiC-SC key performance indicators (KPIs) (e.g., project duration, MiC-SC costs, and emissions). Moreover, optimizing logistics and construction decisions to achieve a trade-off between these KPIs is yet to be addressed. This study contributes to the MiC-SC knowledge by (1) developing a multimethod simulation model that captures the dynamic behavior of MiC-SC stakeholders through agent-based modeling and the uncertain interactions between their internal activities and resources using discrete-event simulation and considering more realistic features such as traffic condition, site layout, heterogeneous truck types, and uncertainty of activities duration; (2) integrating the developed model with the Taguchi approach (TA) to identify the significant logistics and construction decisions that impact five KPIs (project duration, construction costs, construction emissions, logistics costs, and logistics emissions); and (3) applying a simulation-optimization (SO) approach to find the near-optimum logistics and construction decisions that maximize the MiC-SC sustainability through minimizing the project duration, total costs, and carbon emissions. The model’s applicability was demonstrated using a case study of a high-rise MiC project. The TA analysis highlighted some interactions between logistics and construction decisions, calling for collaborative decision-making between stakeholders. The proposed SO approach could provide them with near-optimum decisions that minimize the project duration, MiC-SC costs, and emissions.

Off-site construction (OSC) is an innovative construction method that transfers most of the site-based work to a more controlled environment. Construction waste minimization, speedy schedules, higher sustainability, and better quality are some of the perceived benefits of OSC. Therefore, significant research attention has been given to OSC. However, minimal research attention has been given to procurement management in OSC, which could impact its pace of adoption. Existing studies on the procurement methods of OSC projects have overlooked several criteria related to OSC that impact the selection of the appropriate procurement methods (i.e., design-build, construction management, etc.). In addition, the literature lacks decision-making tools to assist OSC practitioners in selecting the appropriate procurement method. In this regard, this study contributes to the body of knowledge by (1) identifying the criteria that impact the selection of OSC procurement methods; (2) developing a multi-criteria decision-making (MCDM) model to select the appropriate OSC procurement methods. The developed MCDM model uses a hybrid approach of analytic network process (ANP) and evidential reasoning (ER). The ANP, which considers the interdependencies among the collected OSC procurement criteria, is used to calculate the relative importance weights through questionnaire surveys. The ER method evaluates various OSC procurement methods in accordance with the criteria importance weights. The results indicate that project quality, cost control, and funding arrangement are the prominent selection factors. On the other hand, the model reveals that the integrated project delivery (IPD) and construction management (CM) methods have the highest utility scores. The MCDM model has been validated by comparing the results with similar studies. The present study could assist OSC practitioners in selecting the appropriate procurement method for OSC projects.

Sustainability has become of great interest in many fields, especially in production systems due to the continual increase in the scarcity of raw materials and environmental awareness. Recent literature has given significant attention to considering the three sustainability pillars (i.e., environmental, economic, and social sustainability) in solving production planning problems. Therefore, the present study conducts a review of the literature on sustainable production planning to analyze the relationships among different production planning problems (e.g., scheduling, lot sizing, aggregate planning, etc.) and the three sustainability pillars. In addition, we analyze the identified studies based on the indicators that define each pillar. The results show that the literature most frequently addresses production scheduling problems while it lacks studies on aggregate production planning problems that consider the sustainability pillars. In addition, there is a growing trend towards obtaining integrated solutions of different planning problems, e.g., combining production planning problems with maintenance planning or energy planning. Additionally, around 45% of the identified studies considered the integration of the economic and the environmental pillars in different production planning problems. In addition, energy consumption and greenhouse gas emissions are the most frequent sustainability indicators considered in the literature, while less attention has been given to social indicators. Another issue is the low number of studies that have considered all three sustainability pillars simultaneously. The finidings highlight the need for more future research towards holistic sustainable production planning approaches.

In modular integrated construction (MiC), the resource allocation problem (RAP) adopted by construction sites and vehicle routing problem (VRP) adopted by logistics companies are highly interdependent. However, this interdependence has been overlooked in the literature. Thus, the plans determined by each problem cannot be achieved practically. Moreover, there is no existing VRP model suitable for the MiC application. This study aims to propose a VRP model suitable for MiC, investigate the interdependence between the RAP and proposed VRP model, and develop a blockchain system to secure information sharing between the RAP and VRP. The first two objectives are achieved by developing a coordinated system formulated as a leader-follower Stackelberg game model (LFSGM). This model is presented as a bi-level optimisation model and solved using a nested ant colony optimisation-based algorithm. The effectiveness of the LFSGM is validated using a real case study. The results show that using the traditional approach (i.e. a separate RAP and proposed VRP) succeeds in providing a plan for the construction sites but not for the logistics company. In contrast, the LFSGM offers applicable plans for both the construction sites and logistics company. Lastly, some managerial implications are identified and discussed.