Supply Chain Analytics最新文献

This study proposes an integrated framework for successfully implementing collaboration strategies in supply chain (SC) management using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and multi-criteria decision-making (MCDM) approach. The study analyses and measures the successful possibility of SC collaboration implementation in small and medium enterprises (SMEs). The fuzzy DEMATEL is used to evaluate the weight of each criterion, and fuzzy MCDM is used to assess the possible success rates of the collaboration strategies. The result shows that top management support and commitment, SC strategic planning, information sharing, goal congruence, organizational compatibility, and decision synchronization are major factors responsible for SC collaboration success in SMEs. This study helps predict the effectiveness of collaboration strategies and indicates remedial activities in the existing collaborative environment by undertaking corrective actions and measures to increase implementation success.

While consolidation strategies form the backbone of many supply chain optimisation problems, exploitation of multi-tier material relationships through consolidation remains an understudied area, despite being a prominent feature of industries that produce complex made-to-order products. In this paper, we propose an optimisation framework for exploiting multi-to-multi relationship between tiers of a supply chain. The resulting formulation is flexible such that quantity discounts, inventory holding, and transport costs can be included. The framework introduces a new trade-off between tiers, leading to cost reductions in one tier but increased costs in the other, which helps to reduce the overall procurement cost in the supply chain. A mixed integer linear programming model is developed and tested with a range of small to large-scale test problems from aerospace manufacturing. Our comparison to benchmark results shows that there is indeed a cost trade-off between two tiers, and that its reduction can be achieved using a holistic approach to reconfiguration. Costs are decreased when second tier fixed ordering costs and the number of machining options increase. Consolidation results in reduced inventory holding costs in all scenarios. Several secondary effects such as simplified supplier selection may also be observed.

Public health agencies and medical organizations have increased their relentless efforts to control the outbreaks of mosquitoes causing West Nile disease epidemics with the re-emergence of deadly disease in the United States. Such measures include a large-scale spray operation of insecticides that can counter the population growth of mosquitoes. This study proposes a business analytics tool that helps determine the optimal number and location of airfields housing insecticide-spraying aircraft, the type (mode) and the number of insecticide-spraying airplanes, and their flight patterns. This study also identifies factors that can enhance and hinder the efficiency of insecticide spray operations by combining a bi-objective integer programming model with a geographic information system and forecasting models within a business analytics framework for the first time.

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.

The research on multi-period optimization using modified interactive multi-objective fuzzy programming for product complaints in pharmaceutical supply chains is new and evolving. This study proposes and develops an integrated multi-period, multi-objective medicine supply chain model in healthcare. The study considers an unknown number of drug manufacturer complaints. The business triad is a term used to describe the combination of the three objectives: time, quality, and cost. The process starts with developing a mathematical model for the business triad. A modified interactive multi-objective fuzzy programming is then proposed for the optimization of the business triad, has been proposed. The proposed method blends expert opinion and experience using fuzzy linguistic variables and a triangle membership function. A numerical example demonstrates the practical application of the proposed model. This study considers a model for fuzzy inventory pharmaceutical products with a two-tier supply chain. This supply chain model aids healthcare decision-makers in acquiring medications that meet the necessary time, quality, and cost standards.

This study proposes a multi-objective Sustainable Supply Chain Network (SSCN) model considering human resources limitations with different levels of expertise. The proposed model includes multiple suppliers, factories, and customers, where the construction of factories is a strategic decision, and determining the amount of production and allocating human resources with different levels of expertise is taken as a tactical decision. Also, the capital recovery factor has been used in the mathematical model to prevent the influence of strategic decisions on tactical decisions. The results from the mathematical models of epsilon limit, Non-dominated Sorting Genetic Algorithm II (NSGA II), and Multi-Objective Particle Swarm Optimization (MOPSO) show that by reducing the amount of shortage, the amount of production has increased, and as a result, the costs of production, supply and distribution and transportation have increased. Also, with the increase in the production and transportation of products, greenhouse gas emissions have also increased. Examining the impact of the uncertainty rate on the Robust Fuzzy Optimization (RFO) model also shows that with the increase of this coefficient, due to the increase in the demand in the network, the total costs of production, distribution, purchase of raw materials, and transportation have increased. Examining different comparison indices between solution methods also shows that heuristic methods have higher efficiency than exact methods. MOPSO is more efficient than NSGA II for the designed mathematical model in these investigations.

This study triangulates three interrelated and interdependent goals. First, we provide a framework to establish the supply chain (SC) theory within the linchpins of the nine waves of sustainability theory. Second, we provide a real-world example of how blockchain operates to support the premise that hacking a blockchain requires very large capacities of computing power. We also demonstrate a method of detecting the possibility of hacking individual nodes that supply information to the blockchain. Third, we utilize the blockchain and gather thousands of data points and prove statistically that the tokenization of the oil and gas industry will increase market liquidity, market volume, profitability, and sustainability while reducing transaction time. The robotic blockchain is investigated as a mechanism for improving the efficiency of natural gas SC resource use through fuzzy modular function hashing and salting algorithms and entropy density.

The increased frequency of purchases and growing distances between the final distribution points of the perishable products and consumers are contributing to multiple handling, high intermediation, and a greater concentration of outlets selling perishables goods. These in turn have increased logistics costs, and inefficiencies in the supply chain. This study presents a modelling framework for locating perishable goods order fulfilment centers (OFC) near the consumer by using population density as a proxy for demand. The centrality and Borda count measures are used to identify optimal locations in perishable goods supply chain networks. We present a case study to demonstrate the applicability and efficacy of the proposed density-based spatial methodology.

This paper aims to model and minimize transportation costs in collecting tree logs from several regions and delivering them to the nearest collection point. This paper presents agent-based modeling (ABM) that comprehensively encompasses the key elements of the pickup and delivery supply chain model and presents the units as autonomous agents communicating. The modeling combines components such as geographic information systems (GIS) routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. ABM models the entire pickup and delivery operation, and modeling outcomes are presented by time series charts such as the number of trucks in use, facilities inventory, and travel distance. In addition, various simulation scenarios are used to investigate potential facility locations and truck numbers and determine the optimal facility location and fleet size.