Vehicle routing in cold food supply chain logistics: a literature review

Designing a sustainable fish closed-loop supply chain network under uncertainty

There is increasing attention to the sustainable development of supply chain (SC) and reverse logistics (RL) in the contemporary competitive economy, notably in the food sector, by scholars and stakeholders. This study investigates a sustainable closed-loop supply chain (CLSC) for fish due to its high value in the family food basket, its perishability, and the importance of waste product recycling. A multi-objective mathematical model is developed under uncertainty and sustainability criteria to optimize production rates with the aim of better distribution among different demand markets, total costs, social issues, and negative environmental effects (e.g., CO2 emissions and unused/waste products). A combination of exact, meta-heuristic, and hybrid meta-heuristic algorithms are used to solve the suggested model. Then, the optimal solutions are found using the Taguchi method by evaluating the best initial replies. The solutions are evaluated based on various performance metrics. The analysis of variance (ANOVA) and the "filtering/displaced ideal solution" methods determine the best solution approach. Moreover, a case study with a trout CLSC in Northern Iran is examined. In addition, the Lingo software utilizes the ε-constraint method to evaluate and check the performance of the algorithms under different levels of uncertainty. Finally, sensitivity analyses are carried out to confirm the efficacy of the proposed algorithms. The findings demonstrate the proposed network's outstanding consistency with the algorithms used and its application and efficiency.

Identification of the Critical Enablers for Perishable Food Supply Chain Using Deterministic Assessment Models

Today’s perishable food supply chains must be resilient to handle volatile demands, environmental restrictions, and disruptions in order to meet customers’ requirements. The enablers of the perishable food supply chain have not yet been explored. In this paper, a bibliometric systematic literature review has been conducted to identify the articles related to the perishable food supply chain. Next, with these identified articles, a map is created with bibliographic data using Vosviewer network visualization software, and then the enablers were identified by conducting keyword co-occurrence analysis. Later, a total interpretive structural modeling (TISM) is employed to analyze the interrelationships among enablers and then determine each enabler’s hierarchies, further representing them in a diagraph. Finally, the identified enablers are classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis, and the graph is plotted. The results obtained from the deterministic assessment model provide the critical enablers for the perishable food supply chain. The obtained critical enablers and their hierarchies provide valuable insights for researchers in the context of perishable food supply chain for further study.

A multi-dimensional robust optimization approach for cold-chain emergency medical materials dispatch under COVID-19: A case study of Hubei Province

For the optimization problem of the cold-chain emergency materials (CEM) distribution routes with multi-demand centers and soft time windows and to solve dispatching materials to medical treatment institutions in various places of the disaster areas under COVID-19, a multi-dimensional robust optimization (MRO) model was proposed, which was solved by a hybrid algorithm combined Pareto genetic algorithm and the improved grey relative analysis (IGRA). The proposed model comprehensively takes into consideration of the cost factors of the cold-chain logistics and robustness of solution with the purpose of minimizing the costs and maximizing robustness. The availability of the proposed approach and hybrid algorithm were thoroughly discussed and qualified through a real-world numerical simulation test case, which was a previous risk area located at Hubei Province. Research results show an average-cost reduction of 4.51% and a robustness increment of 11.69% in addition to consider the urgencies of demand. Consequently, not only the costs can be slightly reduced and the robustness be heightened, but also the blindness of the distribution can be avoided effectively with the demand urgency being considered. Research result indicates that when combining with the specific process of supplies dispatching in the prevention and control, the proposed approach is in a far better agreement in practice, and it could meet the diverse requirements of the emergency scenarios flexibly.

Refrigerated Transport: State of the Art, Technical Issues, Innovations and Challenges for Sustainability

The cold chain is responsible for perishable products preservation and transportation, maintaining a proper temperature to slow biological decay processes. Often the efficiency of the cold chain is less than ideal, significantly increasing food waste and energy consumption. Refrigerated transport is a critical phase of the cold chain because of its negative impact on energy consumption and greenhouse gas emissions. It is estimated that around 15% of global fossil fuel energy is used in the refrigerated transport sector, so there has been a growing interest in the last decades in the optimization of these systems in order to reduce their environmental impact. Vapor compression refrigeration units, usually powered by means of a diesel engine, are the most commonly used systems in road refrigerated transport. This paper provides a review of (a) currently used systems and alternative technologies that could reduce the environmental impacts of road refrigerated transport and (b) optimization models and methods used to minimize fuel/energy consumption and greenhouse gas emissions, focusing both on reducing the thermal loads and solving the refrigerated vehicle routing problem.

Multi-echelon agri-food supply chain network design integrating operational and strategic objectives: a case of public distribution system in India

The global concern to ensure the availability of food for the growing world's population draws urgent attention towards the inefficiencies in agri-food supply chains. Agri-food supply chains are inherently complex to manage than other supply chains mainly because of their multi-echelon structure, deteriorating product quality with time and changes in storage conditions which leads to significant amount of food loss and wastage. Additionally, any natural or man-made disaster further disrupts the chain and leads to high food loss, high supply chain costs, reduced food availability and poor food quality. Hence, there is a need to design resilient and efficient agri-food supply chain network for optimal multi-echelon storage and distribution to reduce food loss and quality degradation. For this purpose, a Fuzzy Multi Objective Linear Program (FMOLP) is proposed in this paper for integrated food procurement, storage and distribution under cost, resilience and quality considerations. The proposed model integrates the short-term operational objective of cost optimization with the long-term sustainable objectives of food loss minimization and resilience maximization. The proposed FMOLP is illustrated using a realistic case of Public Distribution System using the data benchmarked with the numbers reported by the Food corporation of India. The detailed computational analysis carried out in the paper in investigates three categories of problem sizes to compare and contrast the decisions using different strategies and to provide organizational, operational and policy insights on the trade-off between cost, food loss and resilience.