Supply Chain System Model Research Articles

Digital Technology Increases the Sustainability of Cross-Border Agro-Food Supply Chains: A Review

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the ‘antecedent–practice–performance’ conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier.

Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment

Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party.

A coordination model for closed-loop supply chain systems with a single manufacturer and retailer

This paper develops a coordination model for a closed-loop supply chain (CLSC) system consisting of a single manufacturer and retailer where market demand depends on the green technology level, retailer’s selling price, and promotional efforts. The manufacturer manufactures products from raw materials to finished products and adapts them for sale to meet key market demands. Used products from consumers will be returned to the retailer to be processed by remanufacturing under a technology license, and the rest will be returned to the manufacturer for remanufacturing, refurbishing, recycling, or waste disposal. The models are formulated mathematically and constructed under three scenarios – centralized, decentralized, and a Stackelberg game led by the manufacturer. Numerical examples are given to illustrate the results of the developed model. The result suggests that both types of investment can assist the closed-loop supply chain in enhancing its financial and environmental performance. It also suggests that lowering emissions levels through green technology might increase product selling prices, hence increasing sales volume.

Hyperledger Fabric-Based Tea Supply Chain Production Data Traceable Scheme

With the advent of Industry 4.0, blockchain is one of the emerging technologies that can be used in multiple fields, especially in supply chain networks, where it is considered a sustainable concept technology. Because of its decentralization, reliability, transparency, consistency, and traceability, blockchain can challenge existing conventional models in supply chain scenarios. Therefore, this study proposes a framework that integrates the technology of Blockchain 3.0 (Hyperledger Fabric) into the tea supply chain. The concept of data traceability driven by blockchain technology consists of documenting the tea supply chain system, in which the cultivation, processing, and retailing of tea leaves are documented, and optimizing the existing anti-counterfeiting mechanisms. The ECDSA algorithm is used to confirm the identity among the entities located in the Hyperledger Fabric channel, and IPFS technology is introduced to store tea traceability data to solve the problem of data increment in the tea production process. Only the hash value and traceability code of the traceability data are stored in the block. We analyze the relationship between the number of transactions and latency, and we can see the latency time of both write and read transactions. The system tested write transactions and read transactions with a minimum write speed of 0.97 s and a maximum of 6.26 s and a minimum read speed of 0.1 s and a maximum of 4.62 s via Caliper analysis. The experimental results show that the performance analysis sounds good. This study uses distributed theory and service-oriented thinking in its specific application to the tea supply chain system model and takes each entity through a B2B connection to achieve anti-counterfeit traceability in the tea supply chain of a regulatory nature.

Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, based on the structural characteristics of the supply chain system and the logical relationship between production, sales, and storage parameters, a three-level single-chain nonlinear supply chain dynamic system model containing producers, sellers, and retailers was established based on the introduction of nonlinear parameters. Secondly, the radial basis function (RBF) neural network and improved fast variable power convergence law were introduced to improve the traditional sliding mode control, and the improved adaptive sliding mode control is proposed so that it can have a good control effect on the unknown nonlinear supply chain system. Finally, based on the numerical assumptions, the constructed optimization model was parameterized and simulated for comparison experiments. The simulation results show that the optimized model can reduce the adjustment time by 37.50% and inventory fluctuation by 42.97%, respectively, compared with the traditional sliding mode control, while helping the supply chain system to return the smooth operation after the change within 5 days.

Optimisation of the Single-Vendor Single-Buyer Supply Chain System under Fuzzy Demand Using Optimisation–Simulation Closed Loop Technique

This research aims to model and optimise the most applicable supply chain system, which is a single-vendor single-buyer system with fuzzy buyer demand. An optimisation model of the supply chain system under consideration is built by formulating the objective function, which is minimising the joint total cost between a buyer and a vendor. The model is developed on the basis of a simulation system, and optimisation is carried out by utilising a Genetic Algorithm that has been embedded in the simulation system. This technique is called optimisation–simulation closed loop. The vendor actual condition, which deals with uncertain demands from the main buyer and other small buyers, is considered. To analyse timely supply chain events, a simulation system is developed. A new optimisation model for the single-vendor single-buyer supply chain system with fuzzy demand is developed on the basis of the simulation system. The use of optimisation–simulation closed loop is also a new finding. In this study, the optimisation model of the supply chain under consideration is developed by taking into account a specific condition in which the vendor receives demands from the main buyer and other small buyers. Naturally, buyer demand is uncertain and has been modelled using a fuzzy set. The use of optimisation–simulation closed loop enables the supply chain to make the optimum decision when at the steady state condition.

A mixed-integer linear programming model for multiechelon and multimodal supply chain system considering carbon emission

A mixed-integer linear programming model for multiechelon and multimodal supply chain system considering carbon emission

A Conceptual Model for Blockchain-Based Agriculture Food Supply Chain System

In agriculture supply chain management, traceability is a crucial aspect to ensure food safety for increasing customer loyalty and satisfaction. Lack of quality assurance in centralized data storage makes us move towards a new approach based on a decentralized system in which transparency and quality assurance is guaranteed throughout the supply chain from producer to consumer. The current supply chain model has some disadvantages like a communication gap between the entities of the supply chain and no information about the travel history and origin of the product. The use of technology improves the communication and relation between various farmers and stakeholders. Blockchain technology acquires transparency and traceability in the supply chain, provides transaction records traceability, and enhances security for the whole supply chain. In this paper, we present a blockchain-based, fully decentralized traceability model that ensures the integrity and transparency of the system. This new model eliminated most of the disadvantages of the traditional supply chain. For the coordination of all transactions in the supply chain, we proposed a decentralized supply chain model along with a smart contract.

Transformation Model of Smallholder Oil Palm Supply Chain Ecosystem using Blockchain-Smart Contract

The development of new technology has the potential to disrupt and transform an existing system as well as information technology. This study aims to build a proposed model in order to transform an old system into a Blockchain-based system. The smallholder oil palm supply chain currently uses a traditional information system and technology, hence its integrity, transparency, and security are vulnerable. To solve this problem, frontier technology is needed, such as a blockchain, which has trust, transparency, and traceable characteristics to improve performance and quality. The method used in this study was digital transformation in the context of operational processes and technology. In addition, the As-Is To-Be model was used as a mechanism to develop a transformation model for the smallholder oil palm supply chain system. Specifically, the As-Is model was implemented in identifying and analyzing the information system and technology in an already existing system, while the To-Be was used to determine the blockchain potential and characteristics. This becomes the proposed model for the transformation of the old system into a Blockchain technology-based. Also, a prospective and mechanism for system transformation were produced in the aspect of transactions, data, and architecture, as well as the flow of change strategies needed in the transformation of the blockchain-based smallholder oil palm supply chain system.

Green closed-loop supply chain optimization strategy considering CER and incentive-compatibility theory under uncertainty.

Under the uncertain market demand and quality level, a total profit model of green closed-loop supply chain system (GCL-SCS) considering corporate environmental responsibility (CER) and government differential weight subsidy (GDWS) is constructed. Based on incentive-compatibility theory, the optimal subsidy allocation policy and green investment level were explored. Fuzzy chance-constrained programming (FCCP) is used to clarify the uncertainty factors of this model; while genetic algorithm (GA) and CPLEX are used to find and compare a calculating example's approximate optimal solution about this model. The main calculating results indicate that: (1) Enterprises can make optimal recycling, production and sales strategies according to different potential demand; (2) Without government subsidy, enterprises' higher green investment level will reduce their average gross profit, increase the quality level of recycled products and decrease the recycling rate, hence reduce their environmental protection willingness; (3) Based on incentive-compatibility theory, when government subsidy weight is set as 0.34~0.41 for consumers, enterprises' higher green investment level will enhance their average gross profit, reduce the quality level of recycled products and increase the recycling rate, which will improve their environmental protection willingness; (4) Under uncertain environment, the combination of reasonable government subsidy policy and enterprises green investment can make up for the defect of enterprises green investment alone, maximize utilities of government and enterprises, and optimize the green closed loop supply chain.

Supply Chain System Model of Components for Assembly Lines Based on Kanban and Milk Run Methodologies

Seeking to optimize the raw material supply for the assembly lines in many industries, the following case study, starting with a direct observation of a motorcycle factory and an electronics assembly factory, based on a rich theoretical analysis of the Lean wastes, describe the factories present processes and focus on developing a fast, feasible and low cost solution, gathering concepts of Kanban and Milk Run methodologies, resulting in a proposal of a system of real time management of the production status, allowing a better organization for the logistics teams of the named companies.

Supply Chain System Model of Components for Assembly Lines Based on Kanban and Milk Run Methodologies

Seeking to optimize the raw material supply for the assembly lines in many industries, the following case study, starting with a direct observation of a motorcycle factory and an electronics assembly factory, based on a rich theoretical analysis of the Lean wastes, describe the factories present processes and focus on developing a fast, feasible and low cost solution, gathering concepts of Kanban and Milk Run methodologies, resulting in a proposal of a system of real time management of the production status, allowing a better organization for the logistics teams of the named companies.

A closed-loop supply chain inventory model with stochastic demand, hybrid production, carbon emissions, and take-back incentives

This paper considers a two-echelon inventory model for a closed-loop supply chain system containing a manufacturer and a retailer under a stochastic environment with carbon emission reductions. Production and remanufacturing are performed simultaneously in a manufacturer's hybrid production system involving green production and regular production. To encourage the manufacturer to reuse products, the government offers a take-back incentive operating under a collection rate target. Motivated by this offer, the manufacturer significantly improves the system and makes an investment to increase the number of used products collected from the customers. The emissions generated from transportation, production, and storage activities are incorporated into the model and intended to be reduced by a carbon tax regulation. To achieve this, a mathematical inventory model that aims to minimize the joint total cost is built and solved using an efficient procedure. The results show that by controlling the collection rate and the production allocation, the system can minimize the cost and the emissions. Further, the take-back incentive and the manufacturer's investment in collection efforts can effectively increase the return rate of used products, but these policies will lead to an undesirable increase in total emissions.

Sistem Jaminan Mutu dan Prediksi pada Rantai Pasok Ikan dari Perikanan Sungai

The supply chain system with quality assurance and fish prediction has important role for producers and consumers regarding the need for fresh fish to be consumed in certain size. The research aims to design quality assurance and predictive model for the fish supply chain system so that it is always available to consumers. The Fuzzy Tsukamoto method approach is used to design prediction model for required fish based on the fish provided by fishermen, and Fuzzy Mamdani approach is used to design model for quality assurance of fish needs that consumers need every week and month. This supply chain system is designed with upstream fishermen and fish sellers and as downstream fish retailers and fish consumers, while data analysis uses quantitative data sourced from fishermen and fish sellers and fish consumers. The prediction system and fish quality assurance provide output as a material for decision making in order to obtain information for agents and consumers that they can provide and supply fish as needed. A case study was conducted on the river fishery sector in Kota Bangun District.

A system dynamics approach for analyzing supply chain industry: Evidence from rice industry

The rice industry policy must be comprehensive with a scope of policy from upstream to downstream. In other words, it must cover all supply chains of the rice industry consisting of five levels, such as, the level of farmers who process rice, grain traders, rice traders, rice traders in production areas and rice traders in urban markets.The purposes of this research are (1) to identify and model the current supply chain system of the rice industry; (2) analyze the simulation of the rice industry supply chain system policy; and (3) recommend rice industry policies which provide incentives for all rice industry supply chain actors. The research method used is the case study method. The aim is to understand a phenomenon in the rice industry supply chain system in depth in West Java Province – Indonesia. The results show that the rice industry supply chain system model is a closed cycle consisting of material flow feedback in the form of grain, rice, money and information flow in the form of demand that occurs in the interaction of actors from farmers, grain traders, rice milling units (RMU), rice traders in production centers to rice traders in urban wholesale markets in Bandung and Jakarta. Every businessman in the rice industry has the same goal, which is to maximize the profits. Thus, it can potentially lead to a conflict of interest which is manifested in the desire of every businessman to sell as much as they produce at the highest possible price but this will not happen because of the limited resources they have, such as capital and the market demand they receive. The strategy of increasing production is often carried out by the government at this time which it cannot be done partially without considering other rice industry supply chain instruments. The impacts of this partial policies are farmers, collectors, rice traders and rice mills gain unstable profits and the benefits received are lower than before the production strategy and policy were implemented. The recommended policy strategy is the rice industry supply chain system should be able to guarantee the availability of sufficient rice and capable of guaranting the welfare of farmers with a policy that integrates rice farming and agro-industry production strategies, financing strategies and accessible to all levels of actors in the rice industry supply chain, human resource development strategies and rice business risk management strategies, simultaneously. The integrated policy strategy needs to be carried out since rice supply chain management is a coordinating system of material flow in the form of grain, rice, money, facilities and information flow in the form of orders or requests, knowledge and innovation.

Simulation and Analysis of the Complex Dynamic Behavior of Supply Chain Inventory System from Different Decision Perspectives

Based on the local decision perspective and the global decision perspective, considering the limitation of supply capacity and prohibiting returns, the system dynamics method is used to establish a nonlinear supply chain system model. We use the Z-transform theory to transform the dynamic transfer equation into a block diagram, build a supply chain system simulation model, and use it to conduct simulation experiments. The Wolf reconstruction method is used to calculate the largest Lyapunov exponent (LLE) value of each node or combined system to judge the stability of the system. Based on different decision-making perspectives, under different combinations of safety stock factors and demand scenarios, the adjustment coefficients’ decision-making schemes that keep each node in a stable state are obtained. Then, we comparatively analyze the inventory changes of each node and combined system in a stable state under different decision-making schemes.

Research on green closed-loop supply chain with the consideration of double subsidy in e-commerce environment

Issues such as shortage of resources, degradation of environment, enhancement of consumers’ environmental awareness and their preference for green products, continuous improvement of environmental protection laws and regulations of government, together with increasing competition among enterprises, make the construction of green supply chain, such as production, recycling and remanufacturing of environment-friendly products particularly important. However, there are still many constraints for enterprises to effectively implement green supply chain management, such as lack of research and development (R&D) funds and technical capacity. Moreover, government is also eager to know how to formulate effective financial subsidy policies to encourage manufacturers to actively build green supply chain. In the context of above issues, the maximum total profit model of green closed-loop supply chain system is constructed under the consideration of online and offline sales modes and consumers’ green preference in this paper. Considering excessive computational time required when solving this non-linear optimization task with mixed continuous/integer variables via traditional optimization methods, meta-heuristic approaches, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are adopted to try to find and compare calculating example’s approximate optimal solution. The calculating results indicated that enterprises could arrange the ratio of manufacturing and remanufacturing lots properly to achieve system optimal outcome; and government could adopt a suitable subsidy policy to encourage recycling and remanufacturing of used products. Sensitivity analysis of green degree of the recycled products proved that government could adopt the second subsidy strategy for low-green products to further promote the recycling and remanufacturing of enterprises. This research provides theoretical foundation for initiating reasonable government subsidy policy, formulating practical production and operation plan of enterprises as well as maximizing profits in E-commerce environment.

Whole cycle disruption analysis of petroleum supply chain (PSC) based on UASNs monitoring

This paper proposes a whole cycle analysis method of supply chain disruption based on underwater acoustic sensor networks (UASNs). Firstly, the UASNs are deployed to monitor offshore disruptions (such as oil leakage), and the monitoring data of underwater disruptions can be obtained. Based on the monitoring data, scenario inference and Bayesian network forecasting are applied to reversely infer the upstream causes and probabilities of the disruption, which will provide decision-making basis for the effective prevention of such disruptions in the future. At the same time, based on the monitoring data via UASNs, the DA-NET model of the petroleum supply chain (PSC) system is built and the impact of the disruption on PSC operation is analyzed quantitatively, such as cost increase or time delay. The results show that with disruption monitoring via UASNs, the proposed method can not only infer the causes of a disruption, but also quantitatively determine the impact of the disruption on the operation of PSC, which has certain guiding significance for the enterprise managers of the PSC to prevent such disruptions in advance and to deal with them afterwards.

Coordination of a three-level supply chain with variable demand and order size dependent trade credit in healthcare industries

In a traditional inventory model, the customer who purchases the goods is expected to pay the seller immediately. However, in many practical situations, the seller will give the customer a reasonable postpone period when the customer’s request amount surpasses a given limit. Now-a-days, the time-dependent demand plays a vital role in the healthcare industries. This paper, we generalized an order linked trade credit approach in three-level supply chain system, including the pharmaceutical manufacturer, the wholesaler and, the hospitals are involved. The pharmaceutical manufacturer gives a permissible delay period to the wholesaler and, the wholesaler likewise gives an order linked trade credit policy on the hospital. This entire investigation is examined in a pharmaceutical stock model for time-dependent production and time-dependent demand of healthcare industries. We outline the pharmaceutical model of three-level supply chain system with cost minimization to decide the optimal cycle time. Further, we decide the optimal cycle time, optimal order quantity and optimal payment time. The model is solved analytically by minimizing the total annual inventory cost of the centralized supply chain model. To delineate the pharmaceutical inventory models the numerical examples are provided. The sensitivity analysis is carried out for parameters and, the managerial implications are also obtained.

Fuzzy Emergency Model and Robust Emergency Strategy of Supply Chain System under Random Supply Disruptions

For random distributors under supply disruptions caused by emergency incidents, a fuzzy emergency model and a robust emergency strategy of the supply chain system are studied. First, for a kind of supply chain system composed of a strategic manufacturer, a backup manufacturer, and multiple distributors, the basic emergency models, including the inventory models and a total cost model, are constructed under random supply disruptions. Then, based on the Takagi‐Sugeno fuzzy system, the basic emergency models of the supply chain system are converted into a discrete switching model, which can realize soft switching among the basic emergency models. Furthermore, according to the different inventory levels, the strategic manufacturer’s production strategies and the distributors’ ordering strategies are designed to reduce the inventory costs of the node enterprises in supply chain system. Second, by defining a discrete piecewise Lyapunov function in each maximal overlapped‐rules group, a new fuzzy robust emergency strategy for the supply chain system is proposed through the principle of parallel distributed compensation. This emergency strategy can not only restore the impaired supply chain to the normal operation state but also keep the total cost of the supply chain at a low level and guarantee the robust stability of the emergency supply chain system. Finally, the simulation results illustrate the effectiveness of the proposed fuzzy robust emergency strategy of the supply chain system.