Supply Chain Of Perishable Products Research Articles

Impact of cap-and-trade regulation on coordinating perishable products supply chain with cost learning

<p style='text-indent:20px;'>This paper incorporates carbon emission regulation and cost learning effects to examine a manufacturer-retailer supply chain for deteriorating items over a multi-period planning horizon. We investigate their impacts on supply chain coordination under the assumption that the product demand is affected by the selling price, promotional effort and inventory level. We first propose two algorithms for determining optimal solutions of the centralized and decentralized models. We show that the decentralized system can be coordinated perfectly with a two-part tariff contract. Further, we study necessary conditions under which members of the supply chain can accept this contract. At last, we conduct numerical experiment to illustrate the obtained theoretical results in impact analysis and the robustness of the coordinated model.</p>

Use of blockchain technology as supply chain management system involving air transport

This article explores Blockchain Technology, and how it can be used in the context of information exchange between stakeholders in international supply chains and networks involving air transport. The article reviews the global experience with this technology of iconic companies (Maersk, Lufthansa, Walmart, Unilever, Nestle, Samsung, British Airways) in logistics and supply chain management. It highlights the features of international chains using air transport, which predominantly consist of two categories of goods: goods with high added value (electronic devices and their components, fashion industry products, jewelry) and goods with strict delivery time requirements (pharmaceuticals, live animals, perishable products, e-commerce products and mail). The study shows that perishable goods have great potential for increasing airline cargo turnover. However, at present, there is no single universal tool for managing their supply chains since the tools used (ERP, SRM, TMS, WMS) do not provide complete transparency of information exchange between all stakeholders. The most problematic stage in the delivery to control steps in the delivery of perishable goods by air occur on the ground, while goods are being handled at the airport of departure and the airport of destination. Difficulties arise while checking the correctness of paperwork, labeling and information authenticity about the product origin. The article suggests using block chain blockchain technology in combination with IoT and smart-contract technologies for SCM of perishable products using air transport. The use of this technology allows to reduce the time of document verification procedures. Customs clearance and phytosanitary control could be vastly improved. Overall tracking and monitoring of a product from the moment of its production to the destination simplifies the identification of any counterfeits, improves the quality of food safety control. A greater level of control becomes possible in logistics operations, to determine liability in possible delivery conditions’ violations cases. Overall optimization of the logistic processes, automatization of the execution of verified financial transactions can be achieved. The use of these technologies in combination with innovative technologies for food quality control will significantly reduce logistics costs in the supply chains of perishable products.

General lot-sizing and scheduling for perishable food products

General lot-sizing and scheduling is a well-studied problem in the literature, but for perishable or time-sensitive products is less investigated. Also, most of studies on perishable product supply chains focus on strategic and tactical decision levels rather than operational decision level and integrated operational and tactical decision levels. We focus on a general lot-sizing and scheduling problem faced by perishable food products. The lifespan and shelf life are two important key features of perishable products that are considered in the problem. This problem can be described as a multi-product, multi-parallel line, multi-period general lot-sizing and scheduling problem with sequence dependent change over time. The objective function is sum of production costs, inventory holding costs, waste costs, and lifespan related cost function. We apply two mixed-integer programming based heuristics to solve generated instances. The heuristics are compared in terms of solution quality and computational time. Also, the sensitivity analysis is presented to analyze the effects of parameters’ changes.

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in the model. The priority index quantifies the qualitative social aspects, such as coordination, trust, behavior, and long-term relationships among the stakeholders. In a multi-echelon supply chain, the performance of distributor/retailer is affected by the performance of supplier/distributor. The priority index measures the relative performance index of each player within the supply chain. The maximization of priority index ensures the achievement of social sustainability in the supply chain. Moreover, to model cost uncertainty, a time series integrated regression fuzzy method is developed. This research comprises of three phases. In the first phase, a mixed-integer multi-objective mathematical model while considering the cost uncertainty has been formulated. In order to determine the parameters for priority index objective function, a two-phase fuzzy inference process is used and the rest of the objectives (cost and GHG) have been modeled mathematically. The second phase involves the development of solution methodology. In this phase, to solve the mathematical model, a modified interactive multi-objective fuzzy programming has been employed that incorporates experts’ preferences for objective satisfaction based on their experiences. Finally, in the third phase, a case study of the supply chain of surgical instruments is presented as an example. The results of the case provide optimal flow of products from suppliers to hospitals and the optimal sequence of the visits of different vehicle types that minimize total cost, GHG emissions, and maximizes the priority index.

An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network

The transition to sustainable supply chains in industries where perishable products are prominent requires advanced models for logistics management. In this paper, a model of integrated location, routing, and inventory problem, the three key problems in optimizing a logistics system, is introduced. Considering the particular decision-making environment of such industries, we give a two-phase approach to incorporate the three dimensions of sustainability into supply chain practices. After identifying more sustainable-oriented suppliers, a problem is formulated as a multi-objective Mixed-Integer Programming (MIP) model to assist in planning a sustainable supply chain. Based on the proposed two-phase approach, we contribute to the current literature by simultaneously addressing different challenges, e.g., sustainability issue, integrated decision-making on location, routing, and inventory control planning, and real-world assumptions to make further advances in both research and practice. Since finding the optimal solution for this problem is a NP-hard problem, two hybrid metaheuristics as parallel and series combinations of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized to solve the problem. The implementation of a set of test instances demonstrates the superiority of the parallel hybridization over the series one. Furthermore, it is observed that when the goal of sustainability is approached, manufacturing sector tends to be decentralized and the local commodity production in more medium- and low-developed locations can exhibit the best sustainability performance.

The design and planning of an integrated supply chain for perishable products under uncertainties

PurposeThis paper aims to design an optimal supply chain network and to develop a suitable distribution planning under uncertainty for perishable product's supply chain. The ultimate goal is to help in making decisions under uncertain environments.Design/methodology/approachIn this paper, stochastic programming is used under conditions of demand, supply and process uncertainties, and a non-linear mathematical model is developed for perishable product’s supply chain. Authors’ study considers disruptions in transportation routes and also within the facilities and investigates optimal facility location and shipment decisions while minimising the total supply chain cost. A scenario-based approach is used to model these disruptions. The retailer level uncertainty due to demand-supply mismatch is handled by incorporating the newsvendor model into the last echelon of supply chain network. In this paper, two policies are proposed for making decisions under uncertain environments. In the first one, the expected cost of the supply chain is minimised. To also consider the risk behaviour of the decision maker, authors propose the second policy through a conditional value-at-risk approach.FindingsAuthors discuss the model output through various examples that are provided via a case study from the milk industry. The supply chain design and planning of the disruption-free model are different from those of the resilient model.Practical implicationsAuthors’ research benefits the perishable products industries which encounter the disruption problems in their transportation routes as well as in the facilities. Authors have demonstrated the research through a real-life case in a milk industry.Originality/valueThe major contribution of authors’ work is the design of the supply chain network under disruption risks by incorporating aspects of product perishability. This work provides insight into areas such as the simultaneous consideration of demand, supply and process uncertainties. The amalgamation of newsvendor model and the approximation of the non-linearity of retailer level cost function especially in the context of supply chain under uncertainty is the first of its kind. We provide a comprehensive statistical study of uncertainties that are present in the supply chain in a unique manner.

A three-echelon supply chain for economic growing quantity model with price- and freshness-dependent demand: Pricing, ordering and shipment decisions

The demand for perishable food products is often influenced by the selling price and the age of the items. This is because perishable food products have become commodities from consumers’ point of view, hence, there are very little differences between competing brands. Consequently, factors like price and freshness (or age) become important determinants of consumer demand. This fact has been used to develop several models for managing perishable inventory. However, most of these models were developed from the perspective of a retailer. Today’s increasingly competitive business environment has forced companies to collaborate with fellow supply chain members in an effort to improve profitability and operational efficiency. With this in mind, this article presents a model for managing inventory in a perishable food products supply chain that begins with farming operations where live inventory items are reared and ends with the consumption of processed inventory. The farming and consumption (retail) stages are connected by a processing stage during which live inventory is processed into a consumable form. Consumer demand at the retail stage is a function of the selling price and the freshness of the processed inventory. The farming, processing and retail stages are the three-echelons of the proposed supply chain aimed at maximising the joint supply chain profit. Through a numerical example, the benefits of jointly optimising the inventory replenishment policy (among all three echelons) are quantified by comparing the network performance of a joint optimisation approach (i.e. centralised) to that of an equivalent independent (i.e. decentralised) optimisation policy.

The effect of decision rights allocation on a supply chain of perishable products under a revenue-sharing contract

Using the framework of an economic order quantity (EOQ) model, we study marketing and operational decisions in a two-echelon supply chain in which a retailer and a manufacturer use a revenue-sharing contract to sell a perishable product. The demand function is sensitive to price, sales effort and the age of the product on shelf. We take into account the issue of decision rights allocation with respect to both sales-effort investment and replenishment policy. In particular, we investigate and compare the performance of the individual parties and of the total supply chain across six scenarios: three in which the investment in sales effort is made by the retailer, and three in which the investment in sales effort is made by the manufacturer, where in each group the cycle length is set either by the retailer, by the manufacturer or in a cooperative manner. We show that when one party determines the cycle length, there are certain conditions under which a two-part tariff contract can be used by the other party in order to influence the cycle length decision, and thus to increase its profits. In addition, we show that there are cases in which both parties benefit when the manufacturer is responsible for investing in sales effort, such that it is in the retailer's interest to give up her decision right in this regard.

Determination of the optimal sales level of perishable goods in a two-echelon supply chain network

In recent years, Supply Chain Management (SCM) has been the main focus in many industries in order to decrease costs and improve efficiencies. In today’s supply chains, sale determination for a product in a specific time period and for a specific customer is highly considered. The importance of this efficiency is increased when dealing with perishable products, such as blood, vaccine, foods, etc. These products not only have various customers, but they also must be used before perishing. This paper represents a model to determine the optimal sales level of perishable products in a two-echelon supply chain, using a Vendor Managed Inventory (VMI) policy. Based on the literature most studies have considered two-echelon supply chain for perishable products with one buyer. The proposed model is formulated based on one vendor and multiple buyers. Considering buyers’ requests in various periods, this model aims to optimize the sales profit by exact and meta-heuristics methods. Three efficient meta-heuristics including GA, PSO and CPSO are utilized to solve the problem and the results showed the good consistency with the results obtained from exact method. The obtained results show that applying VMI policy on two-echelon supply chain for perishable products is an effective approach to optimize the profitability of the proposed network.

Development of a multi-objective model for the design of sustainable supply chains: the case of perishable food products

The role of sustainability in the function of a company and more specifically a food company is pivotal for its financial performance. The environmental issues as well as the potential economic gains from the implementation of its principles ask for the use of multiple instruments that have been developed to green supply chains. Moreover, social issues also arise and involve the food companies social responsibility, as this can be realized through the supply of fresh products that meet consumption security standards. On this basis, the strategic design of these companies’ supply chains can assists them towards meeting their sustainability objectives as it may lead to the selection of transportation modes, location of entry points and distribution centers, and flows between the nodes of the networks under cost, environmental and social impact minimization criteria. Under this context the purpose of this manuscript is to develop and employ a multi-objective (namely cost, social-time and emission minimization) mixed integer linear programming decision-making model for the network design of sustainable supply chains of perishable food products. The specific model was implemented in the case of a fruits importer in the North-Eastern European region considering its geographical settings. To synopsize and according to our findings the suggested model is an easy to use decision-making tool that leads to a whole set of possible solutions incorporating trade-offs between three aspects of sustainability.

Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption

The perishability of blood platelets complicates the management of their supply chain. This paper studies the impact of energy consumption and carbon emissions of transportation activities in a blood platelet supply chain. Energy consumption and carbon emissions vary significantly, and the effective location-allocation of blood facilities is a key strategy for the optimal use of energy. The total cost of the supply chain for perishable products is minimized when energy consumption is optimized. The proposed model is too complex to be solved with existing methodologies; therefore, mathematical tools are used to solve it. A numerical experiment is carried out to validate the proposed model, and graphical representations are presented for better visualization of the study’s outcomes. The results of the numerical studies confirm that the selected locations of blood facilities are optimal for the maximization of energy efficiency and minimization of the total cost.

An integrated two-layer network model for designing a resilient green-closed loop supply chain of perishable products under disruption

Disruption in the electric power system network can have dramatic effects on supply chain performance in terms of economic and environmental objectives, especially for perishable products. This paper addresses the design of a resilient green-closed loop supply chain network for perishable products under the risk of electric power network disruption. The research has presented an integrated model for the interdependent two-layer network structure as a strategy to mitigate the power disruption risk in order to minimize the expected total network cost and the expected total amount of carbon emissions. Integration of two networks on both objectives along with the effect of products’ lifetime has been analyzed in a real case study of the dairy industry. The results designate that the integration of the two networks leads to improvements in both objective functions. The average total network cost and total carbon emissions have been reduced by 21% and 25% compared to the non-integrated layers, respectively. Furthermore, by increasing the products lifetime, the projected model enjoys higher performance being compared with the non-integrated layers model. This paper concludes that the integrated decision making about the infrastructure networks e.g. power network with the supply chain enjoys economic and environmental benefits for both networks layers under power network disruptions.

Risk propagation mechanisms and risk management strategies for a sustainable perishable products supply chain

Risks are inevitable in perishable products supply chains. Frequent occurrences of risks lead to too many disruptions and thus affect the sustainability of perishable products supply chains. This paper explores the risk propagation mechanisms and puts forward the feasible countermeasures for perishable products supply chains to improve the sustainability, which are tested by use of the case study of the yogurt supply chain in Company L. First, using the Tropos Goal-Risk framework, a perishable products supply chain is modeled, and the risk propagation chain is extracted. Then, the three-dimension model of supply chain risk propagation is proposed to represent the risk propagation mechanisms on the basis of the risk propagation chain, according to which, the complexities of the risk propagation in a perishable products supply chain is analyzed. Finally, the risk management strategies are proposed based on the three-dimension model and by dealing with the complexities. This paper innovatively explores how to improve the sustainable operations of perishable products supply chains from the perspective of risk propagation based on Tropos Goal-Risk framework, which creatively replenishes the risk propagation theory and risk management strategies of perishable products supply chains, as well as provides the technical and methodological supports for the study on the risk propagation mechanisms and countermeasures to improve the sustainability of perishable products supply chains.

Joint advertising and preservation service decisions in a supply chain of perishable products with retailer’s fairness concerns

The prosperity of e-commerce in China complicate the relationships between supply chain members, such as members’ fairness concerns. For perishable products, both advertising and preservation efforts can promote sales performance. This paper presents a dual-channel perishable product supply chain which consists of a supplier and a retailer. To understand the impact of the retailer’s fairness concerns, we formulate a Stackelberg model to analyze the joint advertising and preservation service decisions of the supply chain members. Besides, we compare the supplier and the retailer’s strategies and their revenues in different scenarios. The results show that there exist equilibrium solutions under certain conditions where the retailer is fair neutral or fair-minded. For a fair-minded retailer, expressing temperate fairness increases his revenue, but excessive pursuits of fairness are adverse to himself. Finally, we provide some managerial implications for suppliers and retailers to make supply chain strategies and design cooperation contracts.

A perishable product supply chain network design problem with reliability and disruption considerations

Existing literature in humanitarian aid supply chain management has not examined the impacts of disruption on timely and cost-efficient delivery of perishable products during disasters. This paper aims to contribute to fill this gap from a supply chain network design perspective. The supply chain network under investigation entails suppliers, mobile and fixed warehouses, distribution centers, and customers. A realistic problem is considered in which facilities and routes between them are subject to disruptions and might become inaccessible in the aftermath of disasters. We present a bi-objective robust optimization model that is resilient to disaster scenarios. The proposed model integrates strategic and tactical decisions and aims to minimize the time and cost of delivering products to customers after the occurrence of a disaster, while it considers the possibility of multiple disruptions in facilities and routes among them. A solution approach based on Lagrangian relaxation and ε-constraint is developed to efficiently solve the bi-objective model. To validate the formulation and derive practical insights, we apply the proposed methodology to a real case study of blood supply chains. The resulting analyses focus on: (i) comparing the impacts of disruptions at different facilities and routes, (ii) examining the influence of planning for disruptions on the expected delivery time, (iii) investigating the effects of an increase in budget on the expected delivery time, and (iv) evaluating the performance of the proposed robust model and the solution approach.

Implementation of EOQ and Lambert W function in 1-D engine simulation model for optimizing fuel injection in GDI engine

• A novel and unique approach based on EOQ for optimizing fuel injection is implemented. • A scheme for coupling crank angle resolved model with EOQ in MATLAB SIMULINK. • Predictive combustion model with EOQ is sufficient for optimizing fuel quantity. • Proposes EOQ with Lambert W function for model based engine calibration approach. The aim of this study was to implement Economic Order Quantity method (EOQ) together with the Lambert W function in a 1-D engine simulation model in order to develop a fuel control strategy for a Gasoline direct injection (GDI) engine. Previous work of the co-author demonstrated the possibility of optimizing fuel injection quantity in GDI engine using the EOQ that is commonly used in supply chain of perishable products. This work extends the previous work and implements it in a 1-D, crank angle resolved, engine simulation model for the application of model based calibration process. The present work uses a validated engine simulation model, which is based on predictive combustion modelling approach, and couples the 1-D engine simulation model with SIMULINK to add the evaporation, wall- wetting and heat transfer models . It employs FORTRAN subroutines to modify the internal code of the 1-D simulation software in order to add crank angle resolved evaporation model. Finally, EOQ with Lambert W function was added to the model using MATLAB with special attention to the decimal control for the solution. This study demonstrated that EOQ and Lambert W functions together are a suitable method to develop fuel control strategy for a model based calibration procedure when implemented in crank angle resolved 1-D simulation model.

A resilience model for cold chain logistics of perishable products

PurposeMost of the extant literature on resilience builds on normative, conceptual or silo approaches, thereby lacking an integrative approach to cold chain logistics risks (CCLRs) and resilience. The purpose of this paper is to bridge the current research gap by developing a model, based on broad empirical evidence, of the interplay between CCLRs, resilience and firm performance (FP) in perishable product supply chains (PPSCs).Design/methodology/approachA mixed method approach is used with qualitative data from interviews and quantitative data from a survey across the supply chain. The analysis is framed by contingency theory and resource-based theory.FindingsFour significant sources of CCLRs and six resources used to build resilience are identified. Then, supply chain resilience (SCR) as a moderator of the negative relationship between CCLRs and FP is corroborated.Practical implicationsThe findings will help improve managerial understandings of critical sources of risks in cold chain logistics and resources indispensable to build resilience. The scope of the research is cold chain logistics for PPSCs, which has relevance to other cold supply chains as well.Originality/valueWhile some theoretical frameworks suggest resilience being a moderator in the negative relationship between cold chain risks and a firm’s performance, this study empirically tests this relationship using the survey across the entire supply chain. A new empirically and theoretically driven definition of SCR is also developed.

El Problema de Ruteo e Inventarios en Cadenas de Suministro de Perecederos: Revisión de Literatura

Context: This paper presents a literature review of the Inventories Routing Problem (IRP) applied to supply chains of perishable products. Different approaches to solve this problem are identified and described in terms of structures, models and solution methods. Method: A systematic literature review is conducted searching in different bibliographic databases and selecting the most relevant studies within the period 2004 to 2017. The results are analyzed so as to propose a taxonomy to classify and compare the different approaches proposed to address this problem.Results: We identified that the majority of studies consider heuristic-based algorithms to solve the problem. Because of its computational complexity the methods resort to metaheuristics and mateheuristics combined with exact methods. Regarding the application to specific supply chains of perishable products, they refer mostly to processed foods, medicines, and human blood. The constraints that differentiate this problem from other types of IRP are useful life and deterioration.Conclusions: The conditions and particularities of the supply chain of perishables products imply the need to consider new variables, parameters, constraints and objective functions; in the reviewed studies it is not clearly defined the differences involved when considering the perishability of the products in the supply chain. Future research should take into account the multiple ways in which deterioration is carried out with factors such as temperature, light, oxygen, humidity and in some cases microorganisms. Also include in the models the cold chain, hygiene standards, air pollution, emissions of greenhouse gases, generation of waste, occupation of roads and other aspects related to City Logistics and Green Logistics.

A refined framework of information sharing in perishable product supply chains

PurposeThe purpose of this paper is to contribute to the understanding of the relationship between information sharing and performance of perishable product supply chains (PPSC). Building on transaction cost economics (TCE), organisational information processing theory (OIPT), and contingency theory (CT), this study proposes a theoretical framework to guide future research into information sharing in perishable product supply chains (IS-PPSC).Design/methodology/approachUsing the systematic literature review methodology, 48 peer-reviewed articles are carefully selected, mapped, and assessed. Template analysis is performed to unravel the relationship mechanisms between information sharing and PPSC performance.FindingsThe authors find that the relationship between information sharing and PPSC performance is currently unclear, and there is inconsistency in the positioning of information sharing among constructs and variables in the IS-PPSC literature. This implies a requirement to refine the relationship between information sharing and PPSC performance. The review also revealed that the role of perishable product characteristics has largely been ignored in existing research.Originality/valueThis study applies relevant multiple theoretical perspectives to overcome the ambiguity of the IS-PPSC literature and contributes nine propositions to guide future research. Accordingly, this study contributes to the refined roles of relationship uncertainty, environmental uncertainty, information sharing capabilities, and perishable product characteristics in shaping the relationship between information sharing and PPSC performance.

Cold supply chain logistics: System optimization for real-time rerouting transportation solutions

Transportation of perishable products is critical and imposes a series of challenges to the cold supply chain and logistics operations. The specific challenge to be addressed is the strict monitoring of transportation conditions. This paper provides insights in the logistics decision models associated with the cold supply chain of perishable products. The decision-making is performed in the cloud by temporary virtual machines (VMs) associated with every shipment or series of shipments. The VMs make operational decisions based on evaluating actual transportation conditions and location of shipped products against requirements and initial route and terminal market geographical location. The physical part of the logistics cyber-physical monitoring and control system is represented by integrated RFID-WSN sensor devices traveling with the product and reader checkpoints distributed along the transportation routes. Two types of decisions are considered in the proposed models: stopping transportation and/or rerouting the shipments to a closer location. The implementation of the optimization models for an actual case study, which considers shipments of fresh produce across the continental United States, shows significant savings that could be obtained if producers or third party logistics companies adopt the methodology.