Multiobjective location-routing problem of relief commodities with reliability.

The applicability and efficiency of location-routing problems for relief commodities motivate several researchers to develop optimization models and algorithms with regards to real-world cases. This study by presenting a multiobjective mixed integer mathematical model for the location-routing of the medical relief problem at the time of a disaster, proposes a new extension to this applicable model with reliability considerations. The proposed model focuses on the location of temporary relief centers and delivers the pharmaceutical commodities to centers at the shortest possible time with reliability assurance. The model includes three simultaneous objectives of minimizing response time, minimizing operational costs, and maximizing the reliability of the transportation network. As far as we know, this study firstly optimizes these three objectives simultaneously. Another novelty is to add the uncertainty of the problem. In this regard, the inherent uncertainty is formulated by a scenario-based approach. Considering the multiobjectiveness of the proposed model, the Epsilon constraint method as a solution algorithm has been used to solve the model. Results are tested for numerical examples via different scenarios. The results represent the excellent performance of the model to minimize the costs and to increase the reliability for the proposed location-routing problem of relief commodities.

The role of technology innovation and people's connectivity in testing environmental Kuznets curve and pollution heaven hypotheses across the Belt and Road host countries: new evidence from Method of Moments Quantile Regression.

The Belt and Road Initiative (BRI) is closely linked to the ecological sustainability of the infrastructure ventures that intrinsically include the aspects of climate change and pollution. Though there exists literature on the environmental Kuznets curve (EKC) and pollution haven hypothesis (PHH), very few explore the scope in the light of Belt and Road host countries (B&RCs). Therefore, the study examines the income-induced EKC and Chinese outward foreign direct investment (FDI)-based PHH in the multivariate framework of people's connectivity and technology innovation in B&RCs from 2003 to 2018. The outcome of the study reveals that the observed relationship is quantile-dependent, which may disclose misleading results in previous studies using traditional methodologies that address the averages. Utilizing the novel "Method of Moments Quantile Regression (MMQR)" of Machado and Silva (J Econom 213:145-173, 2019), the findings confirm an inverted U-shape association between economic growth and CO2 emissions only at lower to medium emission countries, thus validating the EKC hypothesis. The Chinese outward FDI flows increase carbon emissions at medium to high emission countries, thereby confirming PHH. The findings also indicate that people's connectivity contributes to increasing emissions while innovation mitigates carbon emissions at lower to medium polluted countries. Moreover, the outcomes of Granger causality confirm one-way causality between economic growth and CO2 emissions, between FDI and CO2 emissions, between people's connectivity and CO2 emissions, and between innovation and CO2 emissions. The results offer valuable insight for legislators to counteract CO2 emissions in B&RCs through innovation-led energy conservation in infrastructure projects while adopting green and sustainable financing mechanisms to materialize mega construction projects under the BRI.