Supply Chain Facilities Research Articles

Economically viable reshoring of supply chains under ripple effect

This paper presents stochastic mixed integer linear programming models for economically viable supply chain reshoring under the ripple effect, that is, for the integrated optimization of supply chain reshoring and supply chain viability. The problem objective is to select supply chain facilities for relocation and backup suppliers for recovery supplies to simultaneously minimize cost, maximize service and enhance viability. If the primary supplier is not selected for reshoring, the viability can alternatively be improved by recovery supplies from the backup supplier. The problem is formulated as a multi-portfolio stochastic optimization. The portfolio of suppliers/plants for reshoring is optimized along with an alternative recovery portfolio of backup supplies. This study indicates that reshoring decisions directly affect supply chain viability and have positive impact on both its average and worst-case performance. The more risk-aversive is viable reshoring (the confidence level greater than 0.90), the greater is also improvement of supply chain business-as-usual resilience. If increase of expected customer service is more important than cost reduction, supplier reshoring is preferable to backup sourcing. The findings also indicate that cost- and service-optimal reshoring decisions are getting closer when the government subsidy for reshoring significantly increases such that the reduced reshoring costs and domestic costs do not exceed the achieved reduction of lost sales and backup sourcing. Then both conflicting objectives can be simultaneously achieved, which is a highly desirable solution of the economically viable reshoring of supply chain. Numerical examples based on a real-world industrial supply chain prove practical usefulness of the proposed stochastic approach and its high computational efficiency.

Evaluating the blockchain-based healthcare supply chain using interval-valued Pythagorean fuzzy entropy-based decision support system

In the current era, blockchain technology has emerged as a novel technique to maintain the operations of healthcare management systems. The global COVID-19 disease has led to increase in the utilization of technology for healthcare supply chain, patient data management, and claims settlement. Data management in healthcare industry is a complex procedure where multiple organizations offer appropriate supply chain facilities in everyday life. Inadequate data handling disrupts the supply chain, which has a longstanding impact on the healthcare region. Blockchain-based solutions are renowned for their ability to produce safe and traceable results and effective in the health sector for secure data retrieval and storage, resulting in more effectual product creation and tracking. These technologies can deliver data provenance, sponsors candid healthcare industry demands, and certifies the immutability of multi direction transactions. Due to involvement of multiple factors/criteria, the selection of an effective blockchain platform-based healthcare supply chain can be treated as a decision support system (DSS) problem. Thus, the objective of this paper is to present a novel interval-valued Pythagorean fuzzy DSS for evaluating the blockchain platforms for healthcare supply chain and selecting a suitable one with respect to multiple criteria and uncertainty. The proposed DSS framework is divided into three stages. First, some fairly aggregation operators are presented to combine the individual’s information and also discussed their desirable characteristics on interval-valued Pythagorean fuzzy sets (IVPFSs). Second, an integrated weighting tool is developed using entropy-based tool for objective weight of criteria and pivot pairwise relative criteria importance assessment (PIPRECIA) model for subjective weight of criteria with IVPFSs. For this purpose, new entropy is presented on IVPFSs. Third, the multi-attribute ideal-real comparative analysis (MAIRCA) model is developed with the combination of fairly aggregation operators, entropy-based weighting tool and PIPRECIA model with interval-valued Pythagorean fuzzy information. Further, the proposed DSS is used on a case study of blockchain platforms for healthcare supply chain evaluation, which confirms its applicability and usefulness. Sensitivity and comparative assessments are carried out to check the consistency, robustness and efficiency of the presented method.

Design a Mathematical Planning Approach to Optimize the Supply Chain Taking Into Account Uncertainties In Distributors

Abstract With the globalization of markets and increasing competition in global markets, the attempts of organizations to survive in this market has increased and has resulted in the emergence of the philosophy of Supply Chain Management. There is uncertainty in the reliability of supply chain facilities for reasons such as natural disasters, terrorist attacks, labor errors, and weather conditions. Therefore, when making strategic decisions, the system will continue to operate with minimal damage. Over the course of this study, the uncertainty of supplier layers in the supply chain has been modeled. To meet that aim, the issue of supply chain, including producers, warehouses, suppliers and consumers are considered. To calculate the cost of breakdowns due to the non-functioning of distributors, the scenario-building method has been utilized. Finally, the desired model is solved with Gomez software and the results are presented. The result of the study demonstrate the efficiency of this model in the facility location decision-making in supply chains.

Two Meta-heuristic Algorithms for Solving Multi-objective Model for the Service Quality and Price in the Digital Supply Chain

Facility location is an integral part of organizational strategy that can play an essential role in the strategic orientations of the organization. This activity includes many factors that may be inherently conflicting, so that if the necessary checks are not made when choosing a location, it can affect the life of the organization in the long run. The purpose of this study is to investigate the location of facilities in the supply chain distribution and develop a new mathematical model for this problem. This research method uses quantitative, the problem instances have been generated with a variety of different conditions and then solved with the proposed model using the exact solution software GAMS. The results of optimizing the supply chain facility location model show that considering long-term decisions simultaneously can lead to a drastic reduction in supply chain costs.

An integrated dynamic model to locate a competitive closed-loop supply chain facility under conditions of uncertainty: A case study of the auto parts industry

With the expansion of competitive markets, supply chain management has become one of the critical issues facing businesses. One of the advantages of sustainable competition for companies is to make supply chain activities more efficient and effective. This paper aims at an integrated closed-loop supply chain (CLSC) problem which is multi-objective, multi-product, multi-period, and multi-level with limited capacities and uncertain conditions of demand and return products. The proposed supply chain network consists of five levels in the forward flow. There are five centers in the backward flow as well. The purpose of this network is to determine the optimal number and location of facilities required in each period and the optimal amount of the transfer flow of products or raw materials through different transportation modes between facilities. In this proposed model, three objective functions are taken into consideration. The first one minimizes all the costs. The second objective function maximizes the quality of products. The third objective function seeks to minimize the sum of deviations from the ideal score of the principal component of each supplier. The data of this research are taken from Pishro Diesel Company. To solve the proposed problem, several methods and algorithms have been used, including unscaled goal programming, boundary objectives, three single-objective meta-heuristic algorithms (PSO, RDA, and TGA), and multi-objective meta-heuristic algorithm (MOGA-II). As the results show, considering products and returned parts in products, a simultaneous practice of forward and reverse supply chains leads to better product quality, less damage to the environment, and lower costs for customers.

Antecedents of agriculture supply chain performance during COVID-19: an emerging economy perspective

COVID-19 led to several complications like labor shortage, inadequate availability of supply chain facilities, price fluctuation, panic behavior, and uncertainty. Despite the challenges, the farmers and stakeholders adopted different strategies for sustaining the agricultural supply chain performance. Hence, the study proposes to explore the antecedents that led to the ASC performance and their linkages. The study combines literature review and qualitative methods to understand and recognize antecedents that impact ASC performance in developing countries. The conceptual model is built with the underpinning theory (the theory of commitment and organization). A quantitative survey follows the study to validate the theoretical model empirically using covariance-based structure equation modeling (AMOS). The ASC performance in the earlier phase of COVID-19 was disrupted. With time, ASC performance was managed by linking different antecedents. The findings reveal the application and linkage of organization theory and theory of commitment which led to ASC performance. The study finds a unique contribution among academia and practitioners by paving directions to manage the uncertainty during COVID-19 and any such risk triggers in the future. The study offers essential insights for practitioners and policymakers to develop a road map for ASC during the calamities.

A Developed Mathematical Model for Designing a Multilevel Sustainable Supply Chain Network Taking into Account Environmental Decisions

In this research, a novel mathematical model for sustainable supply chain network design is proposed. The main contribution and novelty of this research are considering environmentally friendly facilities and several thresholds for emitted pollution, which bring this research closer to real‐world conditions. Since the amount of pollution produced by different supply chain facilities is not the same, it is better to make different decisions regarding each repair and renovation measure, i.e., environmental decisions should be considered step‐by‐step. In addition, the proposed model was optimized by the whale optimization algorithm (WOA) to find the best solution in large‐scale instances in a short and reasonable time. Finally, the performance of the proposed model and the reduction of environmental impacts to improve the stability of logistics systems are reviewed in a case study. The results of the computational analysis show the efficiency of the proposed model.

Marginalization index as social measure for Acetone-Butanol-Ethanol supply chain planning

Most of methodologies for evaluating supply chain have been focused on environmental and economic criteria. Even though, social impact has been addressed in some methodologies, these methodologies have not considered the location where social impact takes place, which is a crucial issue when the social impact is measured. Therefore, the research purpose is to consider the social impact as a function of the supply chain facilities location. This is accomplished through a multi-objective approach for planning of a biomass supply chain considering simultaneously several objective functions: a) the social impact in function the location where it occurs, b) net profit and c) net CO2 emissions. Specifically, proposed mathematical model considers a social objective function based on the marginalization index. Multi-objective approach was addressed via generating several Pareto curves to illustrate the tradeoff between the considered objectives. Maximum reached profit was around $US 13,572 Million per year that can be obtained with two different pairwise analysis. Nevertheless, if the social benefit is maximized, the profit decrease until $US 6000 Million per year. Therefore, results indicate that supply chain entity's location has a crucial effect in the social impact. Additionally, a direct correlation between social functions other objectives was not observed. This approach addressed the lack of studies for the supply chain planning involving social impact functions, which should be multi-factorial. The proposed approach is applied to an important industrial process, the Acetone-Butanol-Ethanol (ABE) process, to contribute to the bioenergy sector developing.

A Desk Study on the Impact of Industry 4.0 on the Supply Chain in India

Industry 4.0 can be simply defined asindustrial work with fully automated concepts. It has established a major impact on the supply chain in India. It has not only automated the production sectors but has also upgraded the typical supply chain into a digital one. The digital supply chain enables a population to gain appropriate products with satisfaction. India is introducing itself as a developing country for the last few years. The major importance of industry 4.0 on the supply chain can be easily seen in India. India is the secondhighest populated country in the world, so the digitalsupply chain is acting as a boon for the country, some valuable projects like Digitalization and Make-in- India have reduced the old policies in the manual supply chain system. This paper presents a desk study on how industry 4.0 has enhanced the digital supply chain in India and helping a large population to get rid of the old school supply chain facility. At the end of this discussion, it can be concluded that industry 4.0 or I4 or smart factory plays an important role in key factors that are responsible for the development stage in India.

Impact of COVID-19 in food supply chain: Disruptions and recovery strategy.

BackgroundThe COVID virus epidemic has produced another era on the planet while we sort out the outcomes in various parts of our everyday life. The food industry and food supply chain do not incorporate an exception. Considering a food supply chain, the business activities and supply of various food products have been suspended due to restriction of demand, closing the food production facilities, financial restrictions.Scope and approachAccording to the spreadability of the pandemic, every nation must understand the seriousness of the circumstance. This work aims to discuss the effect of COVID-19 on socioeconomic implications and the impact of lockdown on the food supply chain and agri-business. The paper also summarizes the suggestions needed to control and deduce the impact of COVID-19. For now, the chance of transmission through the food area is viewed as immaterial, and following Covid in workspaces isn't considered as a need by public authorities. However, the unfriendly impacts on the climate, food frameworks and individuals along the food store network are obvious.Key findings and conclusionA food supply chain facilities should concentrate on facilities like maintenance of employees' safety and health, change of conditions in working. To prevent the increment of food prices, the protectionist policy should avoid. We have also suggested a PDS system to overcome food supply chain disruption. In conclusion, the supply chain should respond and overcome the challenging situation in the food supply chain.

The effect of logistics management, supply chain facilities and competitive storage costs on the use of warehouse financing of agricultural products

This study seeks to analyze the effect of logistics management carried out by warehouse operators, the facilities and access provided to support storage, and the competitiveness of storage costs on the use of warehouse financing by suppliers in Central Java, Indonesia. The sampling method was purposive random sampling. The numbers of respondents involved in this study were 120 suppliers and farmers producing first-rate agricultural products and who are users of warehouse receipts in the Central Java region. By using linear regression analysis with assistance, the study results found that the variables of logistic management, facilities and supply chain access as well as competitive storage costs have positive and significant effects on the use of warehousing financing by suppliers and farmers who use public warehousing. This result confirms that the more precisely warehousing is managed, the higher the level of trust of users involved in the logistics business and supply chain of agricultural products to use additional services in the form of warehouse receipts to support the sustainability of agricultural businesses.

Designing a multi-period production-distribution system considering social responsibility aspects and failure modes

Reliability of facilities and vehicles in a supply chain and the social responsibility are of high importance in designing a supply chain network in many industries; fewer studies have studied the addressed concepts simultaneously. This paper proposes a multi-objective mixed-integer programming model for a multi-period multi-product supply chain considering conflicting economic and social responsibility objectives; furthermore, the reliability of the supply chain facilities and vehicles are integrated into the model rather than separate objectives. The possibility of disruption in the facilities of the supply chain is considered using the exponential distribution together with the effect of social responsibility as a significant pillar of sustainability. Various practical parameters such as accessibility of facilities, unemployment rate, number of created job opportunities, and level of regional development are considered in the modeling framework. Computational analysis is provided using the real dataset of a communication technology company as a case study to manifest the performance of the proposed model. A sensitivity analysis is performed for some specific parameters to recognize the most effective factors of the proposed model. The results can give good guidelines to the practitioners on the importance of considering network reliability and social responsibility as two important issues in network design problems.

Sustainable supply chain network design: An application to the wine industry in Southern Portugal

A case study of the wine industry in southern Portugal was conducted to provide a balanced approach to sustainable supply chain network design. A multi-objective model was developed integrating economic, environmental and social dimensions. The economic objectives include profit and revenue maximisation of the focal winery and minimisation of supply chain costs. The environmental objectives comprise minimisation of greenhouse gas emissions and of water consumption in vineyards and winery. The social dimension encompasses maximising employment and the number of suppliers and facilities. The model optimises the capacity of supply chain facilities, the production rate of wine and its combination, the amount of materials and wine that are moved through the supply chain, and selects suppliers. An achievement scalarizing functions approach was applied to the model, with some reference points projected on Pareto frontiers. The results showed that the current supply chain can be reconfigured and become more sustainable.

Time Based Models for Unit Load Warehouse Control

Many facilities in supply chains have pallets and containers that can be stacked. Stacking containers during material handling can improve the efficiency of warehouse operations; however, this has largely been ignored by researchers. A time-based model is proposed to generate routes that material handling vehicles use for picking and storing containers that includes the ability to stack pallets during transport and to use multi-command operations. For warehouses that store and pick millions of containers each year, small improvements in each trip can have a dramatic cumulative effect on the annual cost savings.

Time-based models for unit load warehouse control

Many facilities in supply chains have pallets and containers that can be stacked. Stacking containers during material handling can improve the efficiency of warehouse operations; however, this has largely been ignored by researchers. A time-based model is proposed to generate routes that material handling vehicles use for picking and storing containers that includes the ability to stack pallets during transport and to use multi-command operations. For warehouses that store and pick millions of containers each year, small improvements in each trip can have a dramatic cumulative effect on the annual cost savings.

A Continuous Approximation Approach Based on Regular Hexagon Partition for the Facility Location Problem under Disruptions Risk

Today’s business environment is complex, dynamic, and uncertain which makes a supply chain facility increasingly vulnerable to disruption from various risk accidents as one of the main threats to the whole supply chain’s operation. However, in general, most of the studies on facility location problems assume that the facilities, once built, will always run availably and reliably. In fact, although the probability is very low, supply chain disruptions often incur disastrous consequences. Therefore, it is critical to account for disruptions during designing supply chain networks. To accomplish planned outcomes and greater supply chain resiliency, this article proposes a continuous approximation approach based on regular hexagon partition to address the reliable facility location problems with consideration of facility disruptions risk. The optimization goal is to determine the best facility location that minimizes the expected total system cost on the premise that the supply chain network is not disrupted as a whole when one or some facilities are subject to probabilistic failure. Our numerical experiment discusses the performance of the proposed solution approaches which demonstrates that the benefits of considering disruptions in the supply chain design can be significant. In addition, considering the impact of disruption probability estimation error on the optimal decision, the misestimating of the disruption probability is also investigated in this paper.

Modelos de Localización para Cadenas Agroalimentarias Perecederas: una Revisión al Estado del Arte

Context: The problem of locating facilities in supply chains of perishable agricultural products has not been widely addressed, however, this issue in recent years has taken great interest because of concerns about the consumption of fresh and healthy food, important aspect in countries with fruits food producer potential. Method: A systematic review of the state of the art on facility location problems for perishable agricultural products was conducted. The following databases were searched: Science Direct, IEEE Xplore, SpringerLink, JSTOR, Scopus and Google Scholar. From an initial collection of 135 papers obtained with a generic search query for food location, 31 were finally selected for review focusing on food supply chain location model, within a publication date ranging from 2004 to 2015. Results: Based on the review, a typology of variables considered and not considered in models pertinent to conditions relevant to countries such as Colombia, is proposed. Objective functions commonly used, specific restrictions for Food Supply Chain (FSC) and logistical drivers most commonly considered in these models were also identified. Future research, regarding variables to be included in FSC models location for perishables in context of mountainous countries were identified.Conclusions: Strategic decisions such as the location of facilities are of great importance for the design of the fresh food supply chain and its network, given the perishability. However, the issue has been poorly evaluated especially due to the difficulty of modeling and the large number of variables to consider in this type of chain. Models that include the perishability, losses and stochastic behavior of some variables are required. Colombia can benefit from more research in location models of perishable food, particularly the impact on perishability due to its particular conditions of great variety of climates, mountainous landscapes along with a limited transport and road infrastructure.

Optimization and Algorithm of Supply Chain Network Among Enterprise Alliances Based on Robust Model of Supply Chain Network Design

Based on real situations of supply chain network among enterprise alliances, this paper takes certain factors in every round of supply chain into consideration to establish robust model of supply chain network design. Before that, the strategy “decompositioncoordination” is adopted to get solutions optimizing supply chain system, putting focus on the analysis of supplier selection cost and decision-making cost of supply chain facilities, which is integrated and coordinated through activity-based costing. After the model establishment, examples are used to illustrate practicability and effectiveness of the model and algorithm.

Multiple commodity supply chain with maximal covering approach in a three layer structure

Many scholars have already investigated the location problem of supply chain facilities and centres under different conditions. In a three-echelon multiple commodity supply chain, the aim is to fulfil customer demand at a minimum cost by optimising the flow of products from factories to distribution centres (DC) and from DCs to customers. In a situation where there are limited numbers of DCs and each of them covers bounded area, locating DCs for the purpose of, maximising coverage of customers' demand and optimising allocation of the customers to those centres, are quite important. In this research, a three-echelon multiple commodity supply chain model with maximal covering approach that meets the following two objectives through appropriate selection of DC sites is presented: 1) maximise coverage of customer demand; 2) minimise the associated transportation cost required for fulfilment of the customer demand. To address such models in small scales, one can easily apply LP-metric method to make a combined dimensionless objective and solve it with lingo software. Considering the fact that the presented model is an NP-hard problem and cannot be solved in this manner, we apply customised version of a heuristic algorithm named Greedy and clearly indicate its robustness.

Collaboration on technological innovation in Danish fashion chains: A network perspective

With brand owners struggling to compete with new products, physical production processes and sourcing logistics, innovation taking place in retail networks is often overlooked. Networks in retailing are comprised by the brand owner, the varieties of single- and multi-brand stores, chains and departments stores, technology and service providers, ownership structures and local level supply chain facilities. This paper analyses theoretical and empirical views of innovation in international retail networks using lead actors in the (Danish) fashion industry as a case to highlight how this industry maintains branded stores as primary retail channels better than other industries. In order to approach the retail network as an important organisational innovation system in relation to brand owners, the aim of this paper is to characterise key elements of innovation in retail networks. The approach of this work is based on four qualitative studies of medium/larger fashion brand owners and their respective retail and service provider networks. The study shows that innovation in retailing has a continuously emergent character with open-ended strategic design requirements and strong utilisation of relations in business networks. The network comprises an innovation system that focuses on organisational learning and iterative development of the intended technologies. Implications of the current study are suggestions to brand owners, network partners and retailers on how to identify, understand, support and promote innovation via this network through systematic management of the network rather than the innovation itself.