There are 7 tables in total, the task is, to assign routes to the Orders in the "Order List" Table given the restrictions (e.g. weight restriction). - The order list already contains Historical data of how the orders were assigned in the past.

Please refer to https://brunel.figshare.com/articles/dataset/Supply_Chain_Logistics_Problem_Dataset/7558679 for further clarification.

The other 6 tables describe the restrictions imposed on the system. - some customers can only be serviced by a specific plant - plants and ports have to be physically connected. - plants can only handle specific items

Notes:

• The terms "Warehouse" and "Plant" are used interchangeably, essentially a warehouse is a plant.

• This is a (deterministic) optimization problem, there is only one order date since we are only looking at orders from one specific day and trying to assign them to routes/factories.

• We have to ship all the orders to PORT09

• The goal is to schedule routes while minimizing freight and warehousing costs.

• I am also just working on understanding the Dataset, maybe we can have a discussion in the comment section for clarifications.

Acknowledgements:

This dataset was taken from the Brunel University of London Website

Snapshot img

Supply Chain Analytics Market Size 2025-2029

The supply chain analytics market size is valued to increase USD 15.51 billion, at a CAGR of 22.2% from 2024 to 2029. Increased need to improve business processes will drive the supply chain analytics market.

Major Market Trends & Insights

North America dominated the market and accounted for a 38% growth during the forecast period.
By End-user - Retail segment was valued at USD 1.45 billion in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 389.88 million
Market Future Opportunities: USD 15,514.40 million
CAGR : 22.2%
North America: Largest market in 2023

Market Summary

The market is a dynamic and ever-evolving domain, driven by the increasing need to optimize business processes and enhance operational efficiency. A key trend fueling market growth is the rising adoption of predictive analytics in supply chain management. However, the implementation of supply chain analytics comes with challenges, including data security concerns and the need for significant IT investment.
Core technologies, such as machine learning and artificial intelligence, are at the forefront of innovation, enabling real-time insights and forecasting capabilities. In the application space, logistics and inventory management are leading sectors, while regulatory compliance and regional variations add complexity to the market landscape.

What will be the Size of the Supply Chain Analytics Market during the forecast period?

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How is the Supply Chain Analytics Market Segmented and what are the key trends of market segmentation?

The supply chain analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Retail
  Manufacturing
  Healthcare
  Transportation
  Others


Deployment

  On-premises
  Cloud-based


Service

  Professional services
  Managed services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.

In today's dynamic business landscape, retailers are leveraging advanced analytics solutions to gain valuable insights from their supply chain operations. These insights enable retailers to make data-driven decisions, optimize inventory levels, and enhance supplier performance. According to recent studies, the adoption of supply chain analytics in retail has seen a significant increase, with approximately 30% of retailers reporting an improvement in inventory management and a 25% reduction in stockouts. Looking forward, industry experts anticipate that this trend will continue, with up to 40% of retailers planning to invest in advanced analytics tools in the next three years. Predictive modeling and data visualization are essential components of these solutions.

They help retailers analyze historical sales data, market trends, and external factors to accurately forecast demand. Furthermore, AI-powered insights, risk management, and digital twin technology facilitate supply chain design and optimization, while optimization algorithms, network optimization, and performance dashboards ensure efficient operations. Demand planning and forecasting are critical aspects of supply chain analytics. By analyzing demand patterns and lead times, retailers can optimize inventory levels, minimize carrying costs, and maintain stockouts. Moreover, retailers can evaluate their suppliers' performance using statistical modeling and cloud computing solutions. This evaluation includes analyzing delivery times, product quality, and overall reliability, enabling retailers to collaborate more effectively and negotiate better terms.

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The Retail segment was valued at USD 1.45 billion in 2019 and showed a gradual increase during the forecast period.

In the realm of logistics optimization, real-time tracking using IoT sensors and blockchain technology ensures transparency and security. Additionally, linear programming, inventory optimization, production scheduling, warehouse management, order fulfillment, and machine learning algorithms facilitate efficient operations and minimize costs. In conclusion, the application of supply chain analytics in retail is a continuous and evolving process. By utilizing advanced tools and techniques, retailers can optimize inventory levels, enhance supplier performance, and improve overall supply chain efficiency. With the increasing adoption of these s

Supply Chain Management Market Outlook

According to our latest research, the global supply chain management market size reached $28.7 billion in 2024, demonstrating robust momentum driven by digital transformation and increasing complexity in global trade. The market is projected to grow at a CAGR of 11.6% from 2025 to 2033, reaching a forecasted value of $77.2 billion by 2033. This growth is primarily fueled by the rapid adoption of advanced technologies, such as artificial intelligence, blockchain, and IoT, which are revolutionizing supply chain operations and enhancing transparency, efficiency, and resilience across multiple industries.

A primary growth factor for the supply chain management market is the accelerating pace of globalization, which has significantly increased the complexity of supply chains. Businesses are now required to manage vast networks of suppliers, manufacturers, distributors, and retailers across multiple geographies. This complexity necessitates robust supply chain management solutions that can provide real-time visibility, optimize logistics, and ensure seamless coordination among all stakeholders. The ongoing shift towards e-commerce and omnichannel retailing has further intensified the need for agile and responsive supply chain systems, driving organizations to invest heavily in advanced software and automation tools to maintain competitive advantage and meet evolving customer expectations.

Another significant driver is the increasing emphasis on risk management and supply chain resilience in the wake of global disruptions, such as the COVID-19 pandemic, geopolitical tensions, and natural disasters. Organizations have recognized the critical importance of having resilient and flexible supply chains that can quickly adapt to unforeseen events. This has led to a surge in demand for supply chain management solutions equipped with predictive analytics, scenario planning, and end-to-end visibility features. The ability to proactively identify risks, assess their impact, and implement mitigation strategies has become a top priority for companies across all sectors, fueling the growth of the supply chain management market.

Furthermore, the integration of emerging technologies, such as artificial intelligence, machine learning, and blockchain, is transforming traditional supply chain processes. These technologies enable automation of routine tasks, enhance decision-making through data-driven insights, and improve traceability and transparency across the supply chain. For instance, AI-powered demand forecasting and inventory optimization tools are helping businesses minimize stockouts and reduce excess inventory, while blockchain technology is facilitating secure and transparent transactions. The continuous innovation in supply chain management software and hardware is expected to drive market expansion over the forecast period.

From a regional perspective, North America currently dominates the supply chain management market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of leading technology providers, early adoption of digital solutions, and high concentration of large enterprises in these regions contribute to their market leadership. However, Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by rapid industrialization, expanding manufacturing sectors, and increasing investments in digital infrastructure. The region's growing focus on supply chain optimization, particularly in China and India, is expected to create significant opportunities for market players in the coming years.

Data Integration for Supply Chain Execution plays a pivotal role in the seamless operation of modern supply chains. As businesses strive to enhance efficiency and responsiveness, integrating data from various sources becomes crucial. This integration allows for real-time visibility and coordination across different supply chain functions, from procurement and manufacturing to logistics and distribution. By leveraging advanced data integration techniques, organizations can break down silos, streamline processes, and ensure that all stakeholders have access to accurate and timely information. This not only improves decision-making but also enhances the overall agility and resilience of the s

Dataset

This dataset was created by Divyesh Ardeshana

Contents

The supply chain management market size is projected to grow from USD 31.27 billion in 2024 to USD 94.71 billion by 2035, representing a CAGR of 10.60%, during the forecast period till 2035.

The Supply Chain Big Data Analytics Market Report is Segmented by Component (Solution, Service), End User Industry (Retail, Transportation and Logistics, Manufacturing, Healthcare, Other End-User Industries), Deployment Model (On-Premise, Cloud), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Supply Chain Analytics Market is segmented By Component (Solution and Services) and Deployment Mode (Cloud and On-premises)

In 2019, the global next-gen supply chain market generated roughly ** billion U.S. dollars. By 2030, the size of this market is forecasted to more than ******. Next-gen supply chain market refers to the high utilization of the digital revolution by logistics companies or start-ups to enhance the economic and environmental sustainability of supply chain services.

The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been generated according to a normal distribution with the same mean and standard deviation as in the original dataset (e.g. the demand figures have the same mean and standard deviation as those found in the original problem).

In 2023, the Supply Chain Management Market reached a value of USD 29.3 billion, and it is projected to surge to USD 58.7 billion by 2030.

The historical sales dataset for this research is obtained from a Bangladeshi retailer. The dataset covers a period of 1826 days and includes daily sales data for a particular product from 01 January 2013 to 31 December 2017. The raw sales data has 2 columns: the first column contains timestamps, while the remaining column reflects the quantity sold.

The Global IoT for Supply Chain Management Market Size Was Worth USD 21.38 Billion in 2023 and Is Expected To Reach USD 57.6 Billion by 2032, CAGR of 13%.

The global cloud supply chain management market is projected to register a CAGR of 11.1 % by 2034, to reach USD 16.02 Billion in 2034 from USD 6.93 Billion in 2020

The Supply Chain Analytics Market size is expected to reach a valuation of USD 43.0 billion in 2033 growing at a CAGR of 18.00%. The Supply Chain Analytics Market research report classifies Market by share, trend, demand, forecast and based on segmentation.

The supply chain analytics market is likely to record a strong CAGR of 15.1% during the forecast period. As of 2024, the market is valued at USD 7.8 billion. It is slated to surpass USD 31.7 billion by the end of 2034.

Snapshot img

Food Supply Chain Market Size 2024-2028

The food supply chain market size is forecast to increase by USD 59.51 billion at a CAGR of 7.86% between 2023 and 2028.

The market is experiencing significant growth, driven by several key trends and challenges. One of the major trends transforming the industry is the integration of blockchain technology into food supply chain management. This innovation enhances transparency, traceability, and security, enabling consumers to access detailed information about the origin and journey of their food. Another significant trend is the increasing number of mergers and acquisitions among market participants, which is intensifying competition and leading to the formation of larger, more efficient supply chains. However, data security and cyber threats remain critical challenges for market players, necessitating strong security measures to safeguard sensitive information and protect against potential breaches. These factors, among others, are shaping the future of the market.

What will be the Size of the Food Supply Chain Market During the Forecast Period?

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The market encompasses the production, transportation, warehousing, and distribution of a diverse range of food products, including fresh fruits, vegetables, meats, dairy, and processed foods. This market is characterized by its intricate nature, involving temperature-controlled logistics, cold chain management, and adherence to stringent safety regulations. E-commerce platforms have significantly disrupted traditional food trade channels, necessitating advanced technologies such as artificial intelligence, the Internet of Things, and blockchain technologies to ensure efficient and secure food supply.



Agriculture remains a critical upstream component, while downstream activities include transportation, warehousing, and warehouse management systems utilizing positioning systems and radio frequency identification for real-time tracking and inventory management. Consumer preferences for healthier, safer food options continue to shape market dynamics, driving innovation and investment In the sector.

How is this Food Supply Chain Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Product Type

  Packaged food
  Fresh food


End-user

  Households
  Commercial
  Industrial


Geography

  APAC

    China
    India
    Japan
    South Korea


  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  South America



  Middle East and Africa

By Product Type Insights

The packaged food segment is estimated to witness significant growth during the forecast period.

The food supply chain encompasses various sectors, including fresh and perishable foods, food trade, temperature-controlled logistics, e-commerce platforms, and sustainability. Perishable foods, such as meats, dairy, fruits, and vegetables, require specialized handling and cold chain management to ensure safety and quality. E-commerce platforms and consumer preferences for convenience have led to increased demand for customized logistics solutions and multi-modal transportation. Temperature-controlled logistics and cold chain capabilities are crucial for maintaining food safety regulations and product integrity. Advancements in technology, such as artificial intelligence, the Internet of Things, blockchain technologies, and precision farming, are revolutionizing the food supply chain. These technologies enable better inventory management, traceability, and transparency, enhancing consumer trust and product provenance.

Sustainability and economic growth are essential considerations, with a focus on reducing food waste and loss throughout the supply chain. The food supply chain is complex, involving agriculture, food processing, transportation, warehousing, and food retailers. Standards and regulations, including health and safety, positioning systems, radio frequency identification, and warehouse management systems, play a critical role in ensuring food safety and quality. Funding and investment in food supply chain innovation are essential to addressing the challenges of meeting consumer demands while maintaining efficiency, safety, and sustainability.

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The packaged food segment was valued at USD 54.22 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 47% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that sha

Supply Chain Analytics Market size was valued at USD 6.95 Billion in 2024 and is projected to reach USD 25.1 Billion by 2032, growing at a CAGR of 19.20% during the forecast period 2026-2032.Supply Chain Analytics Market DriversThe Supply Chain Analytics market is booming, driven by a perfect storm of business needs and technological advancements. As companies strive for greater efficiency, resilience, and profitability in an increasingly complex global landscape, they're turning to data-driven insights to optimize their operations. The factors below are key to this market's rapid growth.Increasing Complexity of Supply Chain: Today's supply chains are vast, intricate networks spanning the globe. Factors like globalization, reliance on multi-tier suppliers, and a wider geographic footprint have created a level of complexity that traditional management methods can't handle. Analytics become essential for managing this labyrinth of interconnected parts, providing the tools to analyze data from diverse sources and make sense of the flow of goods from raw material to end consumer. Without these insights, businesses risk major inefficiencies and a lack of control over their operations.Demand for Real-Time Visibility: In a fast-paced market, companies need more than just a snapshot of their supply chain; they need a live, high-definition view. The demand for real-time visibility is pushing the adoption of analytics. Businesses want to track inventory, monitor shipments, and check order status as they happen to quickly identify and respond to disruptions. This need for constant, accurate information is facilitated by technologies like IoT sensors, RFID tags, and GPS tracking, which generate the data that supply chain analytics platforms use to provide this essential transparencyAdoption of Advanced Technologies: The rise of sophisticated technologies like AI, machine learning (ML), and big data is a major catalyst for the supply chain analytics market. These technologies are moving analytics beyond simple reporting to powerful predictive and prescriptive insights. AI-driven platforms can analyze massive datasets to accurately forecast demand, anticipate maintenance needs for equipment, and optimize logistics routes in real time. This allows for proactive decision-making, helping companies reduce costs, improve efficiency, and stay ahead of the curve.

The dataset contains contact and description information for local supply chain organizations, offshore wind developers, and original equipment manufacturers that provide goods and services to support New York State’s offshore wind industry. To request placement in this database, or to update your company’s information, please visit NYSERDA’s Supply Chain Database webpage at https://www.nyserda.ny.gov/All-Programs/Offshore-Wind/Focus-Areas/Supply-Chain-Economic-Development/Supply-Chain-Database to submit a request form.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

The global supply chain analytics market size surpassed USD 9.62 billion in 2025 and is projected to grow at a CAGR of over 16.5%, reaching USD 44.3 billion revenue by 2035, attributed to AI and predictive analytics for demand forecasting.

Healthcare supply chain management operates under complex uncertainty, high risk, and the imperative of sustainable resource optimization. This study investigates the underlying mechanisms through which digital intelligence drives strategic decision optimization in healthcare supply chains. Drawing on the Resource Based View (RBV) and Dynamic Capabilities Theory (DCT), we develop a chain mediated model in which innovation capability and supply chain resilience (absorptive, response, and restorative capabilities), serve as sequential mediators. Using structural equation modeling (SEM) on data collected from healthcare supply chain organizations in China, we find that digital intelligence indirectly enhances decision optimization by fostering innovation and resilience in tandem. Specifically, digital intelligence strengthens innovation capability, which in turn activates all three dimensions of resilience, and together these capabilities produce a synergistic effect that sustains decision improvement. Our findings offer practical theoretical guidance for healthcare institutions seeking to deploy digital intelligence technologies, reinforce dynamic process management, and achieve continuous optimization of supply chain decision making.