Food waste reduction and security are the main concerns of agri-food supply chains, as more than thirty-three percent of global food production is wasted or lost due to mismanagement. The ongoing challenges, including resource scarcity, climate change, waste generation, etc., need immediate actions from stakeholders to develop resilient food supply chains. Previous studies explored food supply chains and their challenges, barriers, enablers, etc. Still, there needs to be more literature on the innovations in supply chains that can build resilient food chains to last long and compete in the post-pandemic scenario. Thus, studies are also required to explore supply chain innovations for the food sector. The current research employed a stepwise weight assessment ratio analysis (SWARA) to assess the supply chain innovations that can develop resilient food supply chains. This study is a pioneer in using the SWARA application to evaluate supply chain innovation and identify the most preferred alternatives. The results from the SWARA show that ‘Business strategy innovations’ are the most significant innovations that can bring resiliency to the food supply chains, followed by ‘Technological innovations.’ The study provides insights for decision makers to understand the significant supply chain innovations to attain resilience in food chains and help the industry to survive and sustain in the long run.

This paper deals with a hierarchical solution approach for multi-objective optimisation of an autonomous vehicle-based storage and retrieval system (AVS/RS) warehouse design. As a result of recent technological and Industry 4.0 developments, industries tend to automise their facilities using systems such as AVS/RS, an intra-logistics system, mostly utilised by large distribution centres. Compared to a traditional crane-based automated storage and retrieval system (AS/RS), these systems are more advantageous for having a flexible travel pattern of autonomous vehicles, enabling the designer vary the number of vehicles in the system based on the changed demand environment. Since it may affect the initial and operational costs as well as the system efficiency significantly, it is important to decide on the right warehouse design at first for these systems. In this paper, a multi-objective optimisation solution procedure under a hierarchical approach for the design of an AVS/RS, by considering minimisation of two conflicting performance measures – average cycle time and average energy consumption per transaction – is presented. By this work, it is also aimed to attract the attention of practitioners for the significance of multi-objective performance optimisation. For the multi-objective optimisation, Pareto-optimal solutions are presented.

The aim of this study is to provide a graph-based solution for performance evaluation of a new autonomous vehicle-based storage and retrieval system, shuttle-based storage and retrieval system (SBS/RS), under various design concepts. By the graph-based solution, it is aimed the decision-maker (i.e. warehouse manager) evaluates a pre-defined system’s performance promptly and decides on the correct design concept based on his/her requirements from thousands of alternative design scenarios of SBS/RS. The design concepts include number of bays (NoB), aisles (NoA) and tiers (NoT) for the rack design and arrival rate of storage/retrieval (S/R) transactions to an aisle of the warehouse (AR). The performance of the system is evaluated in terms of average utilisation of lifts and average cycle time of S/R transactions. Simulation is utilised for the modelling purpose. Seven NoT, seven NoB and six AR scenarios are considered in the experiments. Hence, 294 experiments are completed to obtain the graphs. By this study, to the best of our knowledge it is the first time a graph-based solution including comprehensive design concepts of SBS/RS is presented.