Optimization strategies for the integrated management of perishable supply chains: A literature review

Purpose: The main purpose of this article is to systematically review the papers published in the period 2005-2020 about the integration of production, inventory and distribution activities in perishable supply chains. Design/methodology/approach: The proposed research methodology is based on several steps. First, database and keywords are selected, with the aim to search and collect the main papers, dealing with the integration of production, inventory, distribution activities in perishable supply chains. Then, a bibliometric analysis is carried out, to detect: the main publishing sources, the chronological distribution, the most used keywords, the featured authors, about the selected papers. A five-dimension classification framework is proposed to carry out a content analysis, where the papers of the literature review are classified and discussed, according to: supply chain structure, objective, perishability type, solution approach, approach validation. Findings: Interest in the application of optimization models for integrated decision-making along perishable supply chains is strongly growing. Integrating multiple stages of the supply chain into a single framework is complex, especially when referring to perishable products. The vast majority of the problems addressed are then NP-Hard. Only a limited quantity of the selected papers aims to solve real-life case studies. There is a need for further research, which is capable of modeling and quantitatively improving existing supply chains. The potentials of Industry 4.0 are currently little explored. Originality/value: Based on the analysis of the papers published, this article outlines the current state of the art on the optimization strategies for the integrated management of perishable supply chains, which are very complex to be managed. Research trends and gaps are discussed, future challenges are presentedPeer Reviewe

Integrated Production and Distribution planning of perishable goods

Tese de doutoramento. Programa Doutoral em Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 201

Designing sustainable cold chains for long-range food distribution: Energy-effective corridors on the Silk Road Belt

Modern food production-distribution processes represent a critical stressor for the environment and for natural ecosystems. The rising flows of food across growing and consumption areas couple with the higher expectations of consumers for the quality of products and compel the intensive use of refrigerated rooms and transport means throughout the food supply chain. In order to aid the design of sustainable cold chains that incorporate such aspects, this paper proposes a mixed integer linear programming model to minimize the total energy consumption associated with the cold operations experienced by perishable products. This model is intended for food traders, logistics practitioners, retail managers, and importers collaboratively called to design and plan a cost and environmentally effective supply strategy, physical channels, and infrastructures for cold chains. The proposed model is validated with a case study inspired by the distribution of two example food products, namely fresh apples and ice cream, along the New Silk Road connecting Europe and China. The illustrated analysis investigates the effect of alternative routes and transport modes on the sustainability of the cold chain. It is found that the most energy-efficient route for ice cream is via rail over a northern route and, for apples, is via a southern maritime route, and, for these two routes, the ratios of the total energy consumed to the energy content of the food are 760 and 913, respectively. By incorporating the energy lost due to the food quality decay, the model identifies the optimal route to adopt in accordance with the shelf life and the conservation temperature of each product

Last mile logistics in mega-cities for perishable fruits

Purpose: A common problem in mega cities is congestion, due to the size of the automotive park, this makes that the perishable foods decreasing their organoleptic characteristics or increases their losses, which requires considering the effect of time on routing problems. The state of the art demonstrates the need to formulate new routing models that include the specific characteristics of perishable foods in order to reduce their losses. Design/methodology/approach: A mathematical model was formulated based on two classical models: the three-index vehicle flow model proposed by (Golden, Assad, Levy & Gheysens, 1984) and the time window model proposed by (Cordeau, Desaulniers, Desrosiers, Solomon & Soumis, 1999). We proposed a novel VRP Model that permits reductions loss due to the perishable. Findings: The optimum cost is found with AMP® for twenty nodes, six vehicles and six fruits. For more nodes, a two-phase strategy is proposed, first a clustering based on a modified p-median model and then a VRP for each cluster. Research limitations/implications: The results showed the need to investigate multi-objective models, since the performance measures can be efficiency, quality and response capacity; the model can be applied in other supply chains of perishable foods. Social implications: According to FAO in Logistics practices in the last mile generate between 10-30% of the perishable food loss in developing countries’ mega-cities. Originality/value: A last-mile logistics strategy is proposed to manage delivery routes for fresh fruits in mega-cities, considering the effect of congestion through travel time in the perishability function. The new model it uses the flow variable to control the amount of each fruit arriving to each node and the time variable to define fruit waste or loss depending on the time and type of fruit.Peer Reviewe

A multimodal network flow problem with product quality preservation, transshipment, and asset management

In this paper, we present an optimization model for a transportation planning problem with multiple transportation modes, highly perishable products, demand and supply dynamics, and management of the reusable transport units (RTIs). Such a problem arises in the European horticultural chain, for example. As a result of geographic dispersion of production and market, a reliable transportation solutions ensures long-term success in the European market. The model is an extension to the network ow problem. We integrate dynamic allocation, ow, and repositioning of the RTIs in order to nd the trade-o between quality requirements and operational considerations and costs. We also present detailed computational results and analysis

A Robust Two-Stage Stochastic Location-Routing-Inventory Model for Perishable Items

The aim of this study is to develop a robust two-stage stochastic location-routing-inventory model for perishable items. The proposed model is implemented in a two-stage structure. The first-stage decisions determine the establishment of distribution centres and the second-stage decisions identify the other variables of the problem. In order to reduce the effect of different scenarios on the outputs of the problem, the two-stage model is developed to a robust model. Two variability criteria called \u27Partial Lower Deviation from Mean\u27 (PLDM) and \u27Partial Lower Deviation from Target\u27 (PLDT) are considered for the problem. This robust model can manage the variability of different scenarios considering the variability needed for the problem. The summary of the results of the models indicate that the supply cost, the setup cost, the vehicle supply cost, and the production cost comprise 55%, 28%, 3%, and 14% of the total costs of the supply chain, respectively. Similarly, the ratio of net profit margin to the total revenue of the supply chain derived from the division of the objective function by the revenue function is 15%. Among free, fresher first, older first, and mixed policies, the free policy provides the decision maker with more profit than the other three policies since it imposes less constraints on the model

Model-driven decision support to facilitate efficient fresh food deliveries

The delivery of fresh food is challenged by various uncertainties present in daily logistics operations. To facilitate successful operations, this work reviews the recent work on model-driven decision support systems to identify research gaps and derive implications. Introduced systems in literature mainly employ simulation or optimization methods and focus on the consideration of industry specifics such as short shelf lives and the importance of efficient temperature control. Therefore, food quality models are often integrated to enable one to monitor quality throughout supply chain operations and adjust planning procedure respectively. To strengthen research, future work focusing on a stronger consideration of customer-related factors and holistic approaches considering various interdependencies present in fresh food logistics operations are required

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.The authors are grateful to FCT - Fundação para a Ciência e Tecnologia who financially supported this work through the RD Units Project Scope: UIDP/04077/2020 and UIDB/04077/2020

Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit