The transition to modern and ecologically oriented industries requires the application of new approaches and advanced models of logistics management. In this context, horizontal collaboration has recently become a promising and emerging practice for companies intending to improve their freight transportation efficiency and achieve environmental sustainability. This strategy is usually involved in the independent planning of decision-making problems with economic objectives. However, integrated optimisation of planning decisions with environmental considerations is nowadays considered as one of the major challenges to enhance the competitiveness of logistics networks. In this paper, the integrated planning problem of location, inventory and routing to design two-echelon green logistics networks is studied in collaborative and non-collaborative scenarios. The main purpose of this study is to assess the benefits of horizontal collaboration between suppliers in integrated freight transportation optimization by proposing a new decision support tool. A bi-objective Mixed Integer Linear Programming is proposed and adapted to address both distribution strategies. First, a resolution of the several scenarios with a single objective and a comparison of the results are performed. Second, a multi-objective optimization using an aggregation approach is conducted to find a good trade-off between the economic objectives and environmental ones. The experimental results show that horizontal collaboration among suppliers may decrease the total aggregated cost and emissions in the logistics system.

To face the new challenges caused by modern industry, logistics operations managers need to focus more on integrating sustainability goals, adapt to unexpected disruptions and find new strategies and models for logistics management. The COVID-19 pandemic has proven that unforeseen fragilities, negatively affecting the supply chain performance, can arise rapidly, and logistics systems may confront unprecedented vulnerabilities regarding network structure disruption and high demand fluctuations. The existing studies on a resilient logistics network design did not sufficiently consider sustainability aspects. In fact, they mainly addressed the independent planning of decision-making problems with economic objectives. To fill this research gap, this paper concentrates on the design of resilient and sustainable logistics networks under epidemic disruption and demand uncertainty. A two-stage stochastic mixed integer programming model is proposed to integrate key decisions of location–allocation, inventory and routing planning. Moreover, epidemic disruptions and demand uncertainty are incorporated through plausible scenarios using a Monte Carlo simulation. In addition, two resiliency strategies, namely, capacity augmentation and logistics collaboration, are included into the basic model in order to improve the resilience and the sustainability of a logistics chain network. Finally, numerical examples are presented to validate the proposed approach, evaluate the performance of the different design models and provide managerial insights. The obtained results show that the integration of two design strategies improves resilience and sustainability.