Background: The global logistics industry is facing looming challenges related to labor shortages and low-efficiency problems due to the lack of logistics facilities and resources, resulting in increased logistics delays. The Physical Internet is seen as a way to take logistics into the next generation of transformation. This research proposes a Physical Internet-enabled system that allows multiple companies to efficiently share warehouses and trucks to achieve operational efficiency and reduce CO₂ emissions. Methods: We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. The model is tested with real data simulations to evaluate its performance. Results: The results show that compared to the existing model presented in a previous study, our proposed model improves location optimality and distributive routing efficiency and reduces CO₂ emissions by 54%. Conclusions: By providing a well-founded novel model, this research makes an important contribution to the implementation of the Physical Internet by computing optimal logistics hubs and routes as well as providing a solution to cut CO₂ emissions by half.

As tourism village development proliferates in Indonesia, discernible disparities in perceived benefits among tourism and non-tourism stakeholders have been noted, suggesting that the advantages of tourism are not uniformly distributed among the community. Here, social capital, representing interpersonal trust, networks, and shared norms, emerges as a significant catalyst for resolving the identified challenges and securing community endorsement for sustainable village tourism. This investigation aims to explore the role of social capital and the extent of non-tourism actor engagement in facilitating the longevity of a selected Indonesian tourism village. Data concerning social capital and community involvement were procured via questionnaires administered to 270 respondents, the majority of whom were non-tourism actors within the village. The collected data were subsequently scrutinised utilising Structural Equation Modelling (SEM). The study found that while these non-tourism actors are primarily of productive age, their education levels are relatively low and their primary occupations are low-income farming. Intriguingly, these individuals demonstrate substantial social capital despite their lack of direct engagement in tourism activities, which could be harnessed to promote their active involvement in sustainable village tourism. The research further underscores that trust, a fundamental facet of social capital, is instrumental in cultivating community networks and promoting active participation among non-tourism actors. The understanding derived from this research is hoped to provide a basis for policy formulation, aimed at fostering non-tourism actor engagement in tourism-centric activities, thereby allowing them access to the tourism industry benefits, such as secondary income through tourism-related jobs.

This paper aims at evaluating the impacts of Urban Consolidation Centers (UCC) for sustainable city logistics using Adaptive Dynamic Programming (ADP) based multi-agent simulation (MAS-ADP). Economic efficiency and environment friendliness criteria were used to evaluate the sustainability of UCC. The results proved that the implementation of UCC as a sustainable city logistics scheme is efficient in reducing 8% of the total delivery cost for freight carrier and reducing 36% of the total emissions released to the environment. It is also showed that the use of learning agents is essential to demonstrate the successful implementation of the UCC, as it is only in the learning-based simulation, UCC operator could get a profit. Our simulation analysis also confirmed that compared to widely used reinforced learning algorithms (Q-learning), MAS-ADP brought increased accuracy to the evaluations' outcomes of UCC.