Efficient Supply Chain Network Research Articles

Challenges and Strategies for Inventory Management in Small and Medium-Sized Cosmetic Enterprises: A Review

This research paper presents a case study analysis of the inventory management challenges faced by small and medium-sized cosmetic enterprises (SMEs) and the strategies employed to overcome them. The study was conducted through qualitative research methods, including in-depth interviews with managers of SMEs in the cosmetics industry. The findings revealed that the major challenges faced by SMEs in managing their inventory were poor demand forecasting, inadequate storage facilities, and lack of efficient inventory control systems. To mitigate these challenges, SMEs employed strategies such as outsourcing inventory management, adopting technology-driven inventory control systems, and establishing efficient supply chain networks. The study concludes that effective inventory management is crucial for the success of SMEs in the cosmetics industry, and the strategies identified in this study could be useful for practitioners seeking to improve their inventory management practices.

Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model

In recent years, there has been a tremendous increase in environmental awareness, due to concerns about sustainability. Designing an efficient supply chain network that fulfills the expectation of both business owners and customers and, at the same time, pays attention to environmental protection is becoming a trend in the commercial world. This study proposes a theoretical model incorporating vehicle routing problems (VRPs) into the typical CLSC (closed-loop supply chain) network architecture. This combination assists all operators to act more efficiently in terms of environmental protection and profitability. A mixed-integer-linear-programming model for CLSC network design with fuzzy and random uncertain data is developed to achieve the goals. The parameters of the CLSC network are also programmed using hybrid fuzzy-stochastic mathematical programming. The model is for a single product and a single timeframe. Several numerical examples are provided to demonstrate the validity of the proposed mixed-integer-linear-programming (MILP) model. This study also investigated probabilistic possibilities for recourse variables with a trapezoidal fuzzy number using a problem size of four cases. The result indicates that the model performed well in the numerical test, suggesting it can help the operation to be more profitable if this model is implemented in their daily routines.

Blood plasma supply chain planning to respond COVID-19 pandemic: a case study.

The COVID-19 pandemic causes a severe threat to human lives worldwide. Convalescent plasma as supportive care for COVID-19 is critical in reducing the death rate and staying in hospitals. Designing an efficient supply chain network capable of managing convalescent plasma in this situation seems necessary. Although many researchers investigated supply chains of blood products, no research was conducted on the planning of convalescent plasma in the supply chain framework with specific features of COVID-19. This gap is covered in the current work by simultaneous regular and convalescent plasma flow in a supply chain network. Besides, due to the growing importance of environmental problems, the resulting carbon emission from transportation activities is viewed to provide a green network. In other words, this study aims to plan the integrated green supply chain network of regular and convalescent plasma in the pandemic outbreak of COVID-19 for the first time. The presented mixed-integer multi-objective optimization model determines optimal network decisions while minimizing the total cost and total carbon emission. The Epsilon constraint method is used to handle the considered objectives. The model is applied to a real case study from the capital of Iran. Sensitivity analyses are carried out, and managerial insights are drawn. Based on the obtained results, product demand impacts the objective functions significantly. Moreover, the systems' total carbon emission is highly dependent on the flow of regular plasma. The results also reveal that changing transportation emission unit causes significant variation in the total emission while the total cost remains fixed.

Location of facilities and network design for reverse logistics of lithium-ion batteries in Sweden

Estimations of the amount of lithium-ion batteries reaching their end-of-life in 2025 and the amount being recycled indicates large deviations. To enable an efficient recycling process a well-defined and efficient supply chain network for the recovery of discarded lithium-ion batteries must be put in place. This includes analyzing the needs and restrictions of such a network. The aim of this paper is to provide decision support tools, to analyze input, and optimize a future supply chain for discarded lithium-ion batteries. A mixed integer programming model is developed and applied to the Swedish market. The findings show that several aspects will affect a reverse supply chain for discarded lithium-ion batteries, many of which are still uncertain and hard to predict.

Integrated forward/reverse logistics thin-film photovoltaic power plant supply chain network design with uncertain data

Unique features of solar energy, such as the low cost of operation and low pollution, make photovoltaic power plants attractive. Despite the advantages of these power plants, such as low cost of operation and operating without pollution, their high establishment cost compared to that of the conventional fossil fuel-fired power plants prevents their rapid growth. Therefore, designing and optimizing an efficient supply chain network will help to develop the photovoltaic industry. This study proposes a bi-objective model to design and optimize a thin-film photovoltaic power plant supply chain network integrating reverse logistics. The first objective minimizes the costs of supply chain network design, which optimizes decisions from suppliers to disposal centers. The second objective maximizes the efficiency of the data envelopment analysis model to find suitable locations of facilities. As there is uncertainty in electricity demand prediction and perfect foresight is not possible, a fuzzy-robust programming approach is devised to cope with the uncertain parameters. The validity and practicality of the proposed approach are investigated by a case study based on real-world data. Finally, K-Means clustering is incorporated into the model to analyze the installed photovoltaic capacity of different cities in each period. The results show that using an optimistic approach to deal with uncertainty reduces the total cost by 20% in comparison with using a pessimistic approach. The results also provide helpful insights for decision-makers and policymakers in allocating and optimizing the operation of facilities by considering the real-world characteristics of the candidate locations.

A mixed-integer model for the implementation of postponement strategies in the globalized green supply chain network

Modern business traits and global-scale logistics operations have urged companies to devise responsive and efficient supply chain networks to fulfill customer demands all- around the world. However, such operations have increased resource consumption and pollution production, causing more environmental damage. To address these issues, postponement strategies are adopted to enable responsive and more environmentally friendly supply chain operations. However, only a few studies on supply chain optimization considering postponement strategies and environmental issues have been conducted. It motivates this study to propose a mixed-integer model of an integrated green supply chain network (GSCN) for both single and multi-period planning horizons that incorporate postponement concept, and modularized products and processes. Using these models, various speculation strategies coupled with postponement strategies can be analyzed in configuring green supply chain system with mass customization principle subjected to various carbon tax and carbon cap policies under a global supply chain environment. Computational examples of a mass customization notebook computer supply chain show that postponing product differentiation reduces excessive production processes. As a result, the configured supply chain is able to comply with strict environmental policies with just a slight cost increase. This justifies postponement strategies application in configuring eco-efficient supply chain operations.

Design of robust distribution network under demand uncertainty: A case study in the pulp and paper

The design of a supply chain network helps companies in dealing with variability and uncertain evolution of demand over time. An efficient supply chain network may contribute to fulfill the customers’ demands in a quick and least cost manner. Therefore, it is important to solve the problem dealt with in this article concerning the design of the distribution network under demand uncertainty. The problem is to determine which warehouses to open and how much space to rent (outsource) in warehouses owned by third-party logistics providers. This paper presents the development and application of the robust optimization methodology to distribution network design problem under demand uncertainty. The proposed method allows the designer to find a network configuration having a total cost that is robust to typical changes in the geographical distribution of the demand. The Algorithm is an iterative process based on Benders decomposition. At each iteration, the following two steps are performed. In the first step, the global design problem (master problem) is solved to decide on the best use of warehouses according to the information provided by the previous iterations. For a given warehouse configuration and under some restrictions on demand variations, the second step determines the demand that incurred the largest transportation cost, granted that the transportation cost is optimal. These steps are repeated until finding the warehouses configuration that gives the smallest worst-case transportation cost. At each iteration the worst-case transportation cost sub-problem provides new information to the global design problem, such that the latter can improve its robustness. We report numerical results for real size network problems. The main results show that a high level of robustness of the distribution network can be achieved at a relatively low cost.

Combining data envelopment analysis and multi-objective model for the efficient facility location\u2013allocation decision

This paper proposes an innovative procedure of finding efficient facility location–allocation (FLA) schemes, integrating data envelopment analysis (DEA) and a multi-objective programming (MOP) model methodology. FLA decisions provide a basic foundation for designing efficient supply chain network in many practical applications. The procedure proposed in this paper would be applied to the FLA problems where various conflicting performance measures are considered. The procedure requires that conflicting performance measures classified as inputs to be minimized, or outputs to be maximized. Solving an MOP problem generates diverse alternative FLA schemes along with multi-objective values. DEA evaluates these schemes to generate a relative efficiency score for each scheme. Then, using stratification DEA, all of these FLA schemes are stratified into several levels, from the most efficient to the most inefficient levels. A case study is presented to demonstrate the effectiveness and efficiency of the proposed integrating method. We observe that the combined approach in this paper performs well and would provide many insights to academians as well as practitioners and researchers.

Multi-objective stochastic closed-loop supply chain network design with social considerations

Nowadays, operation managers usually need efficient supply chain networks including important design factors such as economic and social considerations. The recent decade has seen a rapid development of controlling the uncertainty in supply chain configurations along with proposing novel solution approaches. By investigating the related studies, this paper shows that most of the current studies consider the economic aspects and just a few works present the two-stage stochastic programming as well as social considerations to design a closed-loop supply chain network. This motivated our attempts to consider economic and social aspects simultaneously by using the mentioned suppositions among the first studies. Another main contribution of this paper is the hybridization and tuning of a number of recent algorithms to address the problem. The results show that the proposed hybrid metaheuristic algorithms outperform the best existing techniques on the majority of case studies.

A Multi-objective Approach for Supply Chain Network Design: Tilapia Pisciculture in Paraná State - Brazil

Abstract Nowadays, efficient supply chain network design is a major issue, which becomes a greater challenge with the need to consider environmental and social concerns in decisions, besides economic issues. This paper develops a supply chain planning model based on a multi-objective framework that considers economic, social and environmental issues. The model is applied to the tilapia pisciculture supply chain in Brazil. A pay-off matrix is derived and an approximation of the Pareto frontier is built using the augmented ε-constraint method. Several non-dominated solutions are generated and analyzed in order to propose the preferable scenarios of supply chain network design.

Risk analysis in transport and logistics

Abstract Globalization and production concentration have led to more efficient supply chain networks, which has led to the emergence of different types of risks. Although most companies have implemented special risk management programs, there may be events that can not be controlled by businesses, and unwanted consequences are not delayed. The reason I chose the title “Risk Analysis in Transport and Logistics” is that I noticed the increasing importance of transport and logistics in the last period. The purpose of this work is to determine the impact of risks in transport and logistics activity, and for that has been achieved a desk research, in which I have analyzed the statistical data from 2016, regarding transport services in Romania. I think that this paper will be useful for all who want to understand the significance impact of risks in transport and logistics activity, representing a suitable source of information in this area.

Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach

Designing a supply chain network (SCN) is an important issue for organizations in competitive markets. In this paper, a novel robust SCN that considers the efficiencies and costs simultaneously is proposed. In order to estimate the efficiency of the producers and distributors, data envelopment analysis (DEA) model is incorporated into SCN. Moreover, to handle the uncertainty in data, a scenario-based robust optimization approach is applied. The proposed model finds out the efficient location of producers and distributors and determines the amount of purchases from each supplier in uncertain conditions. To illustrate the application of the proposed model, a numerical example is solved and results are analyzed.

Genetic Algorithm for Solving Location Problem in a Supply Chain Network with Inbound and Outbound Product Flows

This paper considers a location problem in a supply chain network. The problem addressed in this paper is motivated by an initiative to develop an efficient supply chain network for supporting the agricultural activities. The supply chain network consists of regions, warehouses, distribution centers, plants, and markets. The products include a set of inbound products and a set of outbound products. In this paper, definitions of the inbound and outbound products are seen from the region’s point of view. The inbound product is the product demanded by regions and produced by plants which flows on a sequence of the following entities: plants, distribution centers, warehouses, and regions. The outbound product is the product demanded by markets and produced by regions and it flows on a sequence of the following entities: regions, warehouses, and markets. The problem deals with determining locations of the warehouses and the distribution centers to be opened and shipment quantities associated with all links on the network that minimizes the total cost. The problem can be considered as a strategic supply chain network problem. A solution approach based on genetic algorithm (GA) is proposed. The proposed GA is examined using hypothetical instances and its results are compared to the solution obtained by solving the mixed integer linear programming (MILP) model. The comparison shows that there is a small gap (0.23%, on average) between the proposed GA and MILP model in terms of the total cost. The proposed GA consistently provides solutions with least total cost. In terms of total cost, based on the experiment, it is demonstrated that coefficients of variation are closed to 0.

Coopetitive Supply Chain Relationship Model: Application to the Smartphone Manufacturing Network.

Previous researches for understanding supply chain relationship have mostly focused on its vertical collaboration between buyers and suppliers. However, there have been some instances of volatile and stable collaborative relationships amongst competitors such as Apple-Samsung product manufacturer-component supplier relationship and airline alliances, respectively, which is recognized as coopetition. Even though there have been several qualitative studies and a number of game theory models on coopetition, it is rare to find any attempts on quantitative characterization of such coopetitive dynamic behavior in supply chain relationship. Hence, in this work, we formulated a MINLP model mathematically representing coopetitive relationships in a cost efficient supply chain network. In particular, the coopetition factor was newly introduced to measure the degree of coopetition among supply chain players and determine the optimal level of coopetition to engage in. The utility and practicality of the model were strongly demonstrated using a case study of a hypothetical smartphone supply chain network under different scenarios, thus proposing their strategically viable optimal interactions. Therefore, this exploratory study can herald a new era of global coopetitive business.

Use Of Genetic Algorithms in Supply Chain Management. Literature Review and Current Trends

For the past few decades SCM has been one of the main objectives in research and practice. Since that time researchers have developed a lot of methods and procedures which optimized this process. To create an efficient supply chain network the resources and factories must be tightly integrated. The most supply chain network designs have multiple layers, members, periods, products, and comparative resources constraints exist between different layers. Supply chain networks design is related to the problems which are very popular in literature. The subject of this paper is to present the variants, configurations and parameters of genetic algorithm (GA) for solving supply chain network design problems. We focus on references from 2000 to 2011. Furthermore, current trends are introduced and discussed.

Influence from Balance between Capacity and Load on Different Development Phases of Supply Chain

During a certain time, balance between the supplier’s production capacity and order load can facilitate the successful conclusion of orders and is a significant guarantee for the supply chain’s positive development. This paper exerts an analysis on the influence form balance between capacity and load on the supply chain during its different phases, and it suggests establishing a stable and efficient supply chain network through properly adjusting the supplier’s load level by the demanding party.

Implementing IT in SCM—Understanding the Challenges

Technology offers the potential to change supply chain networks and processes to reduce non-value adding time spent and to support alternative ways of working. An efficient supply chain network can offer substantial improvements in productivity and in customer satisfaction by making available online, real-time information networked around the organization, giving full supply chain visibility. Thus, information is shared within and between the organization and decisions are made on the basis of this shared information. The technology needed to promote and support change, be it large or small, strategic or operational, if used appropriately offers the chance to improve supply chain, in turn, leading to increased productivity and profitability. However, despite the benefits associated with it, implementation of this technology is not always easy. The present study has been undertaken to understand the challenges faced in implementing information technology (IT)in supply chain management (SCM)and logistics. The study was conducted using the survey method. Data was collected through a structured questionnaire from a sample of 80 Indian companies. Perception map and discriminant analysis were used as the tools of analysis.

Effective allocation of customers to distribution centres: A multiple ant colony optimization approach

The global and competitive business environment has identified the importance of a quick and efficient service towards the customers in the past few decades. Distribution centre (DC) plays an important role in maintaining the uninterrupted flow of goods and materials between the manufacturer and customers. The performance of the supply chain network can be easily improved by an effective or balanced allocation of customers to DCs. Improper or unbalanced allocation of customers can lead to the under- or overutilization of facilities and can further deteriorate the customer service. Performance of the DC can be judged on the basis of its ability to provide the right goods, at the right time and at the right place. The lead time or transit time to deliver the goods to the customers is an important parameter for the measuring the efficiency and effectiveness of a particular DC in a supply chain. In this paper, a multiple ant colony optimization (MACO) approach is discussed in an effort to design a balanced and efficient supply chain network that maintains the best balance of transit time and customers service. The focus of this paper is on the effective allocation of the customers to the DCs with the two-fold objective of minimization of the transit time and degree of imbalance of the DCs. MACO technique is a modified form of the traditional ant colony system, where multiple ant colonies cooperate with each other to find the best possible customer allocation pattern for the DC. The proposed technique shows better performance because of its nature of considering both positive and negative feedback in search of optimum or near-optimum results. The developed algorithm based on the proposed approach is tested on a real practical problem and the results are discussed in this paper.

Strategic Internet application trends in supply chain management

The Internet is evolving as a powerful force in the new marketplace where the nexus of competition has changed from individual firms to efficient supply chain networks both between firms and within industries. This study explores Internet adoption patterns and operational applications in US supply chain networks. The data reveal that the integration of the Internet into supply chain management applications has increased and has moved away from indiscriminate application of novel Internet technologies towards becoming a focused endeavor with precise expectations and measurable goals. Specifically, the study finds that Internet usage within supply chains is maturing as evidenced by enhanced and increased productivity, reduced costs and increased profit for participating firms.

One on one: An Interview with Jose Mejia

Journal of Supply Chain ManagementVolume 38, Issue 1 p. 2-2 One on one: An Interview with Jose Mejia Jose Mejia, Jose Mejia Jose A. Mejia is president, Supply Chain Networks for Lucent Technologies. Since joining Lucent in 1999, he has led the implementation of a supplychain vision and strategy that covers the end-to-end provisioning of Lucentsolutions to its global customer base. Effective January 2001, Mr. Mejia became responsible for integrating the supply chain and manufacturing operations into a complete and efficient Supply Chain Networks group. In his current role, Mr. Mejia is responsible for the executive management and oversight of supplier and supply chain engineering and management, product engineering, test and component engineering, procurement, manufacturing, logistics, and distribution for Lucent, as well as for the company's outsourcing and contract manufacturing efforts. Prior to joining Lucent, Mr. Mejia worked for Nortel Networks, Bay Networks, and Ford Motor Company.Search for more papers by this author Jose Mejia, Jose Mejia Jose A. Mejia is president, Supply Chain Networks for Lucent Technologies. Since joining Lucent in 1999, he has led the implementation of a supplychain vision and strategy that covers the end-to-end provisioning of Lucentsolutions to its global customer base. Effective January 2001, Mr. Mejia became responsible for integrating the supply chain and manufacturing operations into a complete and efficient Supply Chain Networks group. In his current role, Mr. Mejia is responsible for the executive management and oversight of supplier and supply chain engineering and management, product engineering, test and component engineering, procurement, manufacturing, logistics, and distribution for Lucent, as well as for the company's outsourcing and contract manufacturing efforts. Prior to joining Lucent, Mr. Mejia worked for Nortel Networks, Bay Networks, and Ford Motor Company.Search for more papers by this author First published: 05 April 2006 https://doi.org/10.1111/j.1745-493X.2002.tb00123.xCitations: 1 Interview by Julie S. Roberts: writer for Inside Supply Management™. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume38, Issue1March 2002Pages 2-2 RelatedInformation