To mitigate car traffic problems, the United Nations Human Settlements Programme (UN-Habitat) issued a document that provides guidelines for sustainable development and the promotion of public transport. The efficiency of the policies and strategies needs to be evaluated to improve the performance of public transportation networks. To assess the performance of a public transport network, it is first necessary to select evaluation criteria. Based on existing indicators, this research proposes a public transport criteria matrix that includes the basic public transport infrastructure level, public transport service level, economic benefit level, and sustainable development level. A public transport criteria matrix AHP model is established to assess the performance of public transport networks. The established model selects appropriate evaluation criteria based on existing performance standards. It is applied to study the Stonnington, Bayswater, and Cockburn public transport network, representing a series of land use and transport policy backgrounds. The local public transport authorities can apply the established transport criteria matrix AHP model to monitor the performance of a public transport network and provide guidance for its improvement.

This paper considers the problem of predicting a supply chain cost for prefabricated building construction under an uncertain situation. Based on the Activity-Based Costing (ABC) method, we establish a computational model to estimate the total cost of the prefabricated supply chain. The model can assist in not only finding the critical areas for cost reduction of the whole supply chain but also analyzing other costs of prefabricated construction projects. Furthermore, we provide a numerical example of prefabricated building construction to validate the results.

Multi-criteria decision-making (MCDM) methods have been extensively employed by researchers in the public transport (PT) sector. While many studies utilize a single MCDM method, employing multiple MCDM methods can achieve more robust results. Furthermore, integrated MCDM methods have the potential to address the weaknesses and limitations inherent in single MCDM method. In this study, we address the limitations of single MCDM methods by integrating the analytic hierarchy process (AHP) with the analytic network process (ANP) to evaluate public transport networks performance. Based on the established public transport criteria matrix AHP model, we identify interdependencies among criteria. The AHP-ANP method is then applied to assess public transport networks in three case study cities in Australia. The sensitivity analysis conducted on both the AHP and integrated AHP-ANP approaches highlights the influence of criteria interdependency. This research contributes to mitigating the limitations of AHP method and applies AHP-ANP model to provide decision-makers with insights to enhance PT network performance and achieve smart PT network management.

This study proposes an optimisation approach to improve multiple-criteria aspiration-level public transportation performance by combining public transport criteria matrix analytic hierarchy process (PTCM-AHP) models and multi-aspiration-level goal programming. The approach uses the PTCM-AHP to calculate the system weights. Based on the weight values, the approach combines the multi-aspiration goal-level selection process in three different ways. The proposed approach was used to optimise public transportation networks in Bayswater, Cockburn, and Stonnington, Australia, to demonstrate the public transportation network performance optimisation process. By controlling the criteria goal value interval, this new approach combines decision-making plans and strategies to optimise various scenarios. The optimisation outcomes can be applied to provide guidelines for improving the performance of public transportation networks.

Public transport (PT) networks face significant challenges in achieving optimal outcomes due to the presence of risk and uncertainty. Despite the importance of optimising PT networks’ performance, limited research has applied risk management tools to tackle this issue. In response, this study presents a three-stage framework to optimise PT networks’ performance in uncertain conditions. First, we establish a PT criteria matrix using an analytic hierarchy process to develop a criteria model and calculate the criteria weightings. Second, we propose a multi-aspiration-level goal programming approach to optimise a PT network’s performance based on the weighted results. To manage uncertainty, we use Monte Carlo simulation to analyse the probability of the optimal solution. Finally, to validate our approach, we apply the three-stage framework to three case study areas in Australia. The results of this research offer significant insights into identifying the likelihood of criteria optimisation scenarios, thereby assisting decision makers in allocating resources for optimising the delivery of PT network performance solutions in accordance with government requirements.