An Amazon employee is seen loading boxes into a delivery vehicle
To make package deliveries more effective, Amazon researchers drew from the vehicle routing problem, which builds upon the traveling salesman problem, one of the most popular combinatorial problems among the operations research community.

The science behind grouping package deliveries

How Customer Order and Network Density OptimizeR (CONDOR) has led to improved delivery routes.

In 2018, Rohit Malshe, an Amazon principal scientist, looked across the street from his home in Portland, Oregon, and spotted two trucks delivering Amazon packages to neighboring houses.

Malshe and his colleagues within Amazon Logistics (AMZL) Research Science and Amazon’s Supply Chain Optimization Technologies (SCOT) organizations had already started developing new methods to synchronize deliveries to neighboring locations. The goal: to avoid situations similar to the one he just observed — multiple trucks visiting the same area on a given day — to improve deliveries and reduce costs.

Related content
How the Amazon Logistics Research Science team guides important decisions related to last-mile delivery.

Important advances had been made by that time. Around 2017, scientists developed a method to group packages delivered to the same address on the same day. When that succeeded, the algorithm expanded to whole buildings.

“Those local optimizations were tackled first, and we solved them rather quickly,” says Malshe.

The next step: develop the concept of a stop consolidation — a chain of addresses linked by a small road segment. For example, a small group of houses in a cul-de-sac may be grouped together and, if two of them order items that will be delivered on the same day, the system will attempt to combine these deliveries into a single truck.

Focusing on the route

Following these initial advancements, AMZL and SCOT scientists turned their attention to optimizing shipment assignment and delivery systems by focusing on the routes.

“Instead of considering one address or building at a time, one should consider all demand assigned to a route, the time spent delivering, and the geographical blocks assigned to a route,” says Andrea Qualizza, a SCOT senior principal scientist.

The researchers drew from the prize-collecting vehicle routing problem (PCVRP), which builds upon the traveling salesman problem (TSP), one of the most popular combinatorial problems among the theoretical computer science and operations research communities.

Related content
Team Passing Through, with three academics working together, earns $100,000 first prize.

“In the TSP, you just want to find the optimal way — or the shortest possible route — to traverse a certain number of locations,” says Weihong Hu, a SCOT senior applied scientist. But as the number of destinations rises, the number of possible routes surpasses the capabilities of even the fastest computers.

For example, in a scenario with 10 destinations, there can be more than 300,000 possible routes. If the number of destinations increases to 15, the number of possible routes expands to more than 87 billion.

The PCVRP is a more challenging variant of the TSP. Imagine a scenario where there are packages sitting at each customer’s door and you send a driver to pick up all the packages they can within a certain time interval. Every package collected adds a “prize” that is equivalent to the cost of assigning that package to a third-party carrier.

“For every package assigned to AMZL, you collect a reward, but you are also spending your time and truck space to do so,” says Malshe.

Deploying CONDOR

The team iterated on this approach over the past couple of years, developing a new algorithm: Customer Order and Network Density OptimizeR (CONDOR).

Qualizza notes that CONDOR solves a problem even harder than the PCVRP: simultaneously determining how orders are split into shipments and the sourcing fulfillment center for each shipment.

“This project uses a combination of various techniques,” says Qualizza. “There is mathematical optimization, local search, capacitated vehicle routing problem solvers — all of that came together because these techniques considered various aspects of the problem and linked them very naturally with the way our systems work."

The breakthrough of CONDOR, Qualizza notes, is its ability to determine the right tradeoff between the levels of complexity and optimality.

While the problem involves a high number of possible decisions per geographical block, the program reduces that number to less than 10 per block.

“You're losing some optimality, but at the same time, you make the problem tractable,” he says. “The key is squeezing enough bits of utility from the current data when it is processed and considering it all together to achieve meaningful improvements.”

Once confident with the prototype, Malshe says, the scientists tested it in production, working side-by-side with engineers to make that happen. In one of the tests performed — a crossover experiment — a few selected cities were divided into two groups: one of them used the new program, and the other didn’t.

That experiment determined that use of CONDOR resulted in roughly 0.5% fewer routing resources required.

“That means that if the whole network needs 50,000 routes without CONDOR, with CONDOR we should need just 49,750 routes,” says Malshe. Applied over Amazon’s extensive trucking network, the potential gains could be enormous.

CONDOR started running in a few delivery stations in January, and expanded to more locations this spring. Now it is deployed across the entire United States, and there are plans to deploy it in other countries within the next few months. The research behind the new program was presented at the 2021 INFORMS Annual Meeting.

How customers benefit

When a customer places an order on the Amazon store, Amazon immediately reserves inventory for it. Within minutes, Amazon’s logistics models evaluate thousands of options for fulfilling the order. Fulfillment location is one variable: a single warehouse may assemble the order if it has all the items; if not, the order can be split into multiple shipments. Amazon also reserves capacity within its transportation network to ensure the order can be delivered on time.

An Amazon employee is seen scanning packages, there are pallets of boxes behind him
Customer Order and Network Density OptimizeR (CONDOR) has led to improved delivery routes by assessing and reassessing customer orders, before they leave a fulfillment center, to identify effective delivery options.

At that point, a decision is made about how the order will be fulfilled, but it won’t necessarily be the final one. There will be opportunities to revisit the decision before the shipment process starts. If a neighbor places an order later that day, for example, the logistics plan may be updated so that the same carrier delivers both orders.

Different programs may work together to make all of that happen. One program will consolidate orders by the customer’s address, for example, so that a carrier visits the address only once if possible. Another will consolidate the orders by buildings and another by groups of buildings.

Related content
Pioneering web-based PackOpt tool has resulted in an annual reduction in cardboard waste of 7% to 10% in North America, saving roughly 60,000 tons of cardboard annually.

CONDOR takes that to the next level by looking at the entire geographic area that a delivery station serves. Every once in a while, the decisions are reevaluated to ensure routes are optimized. From the time a customer places an order to the time it starts being processed by a fulfillment center, it could be five or six hours. During that time span, the CONDOR code might reassess the order three to four times, providing many opportunities for further optimization.

The team estimates that this year alone, CONDOR will help avoid millions of miles driven, boosting sustainability.

“We can enable carriers to deliver more packages to more customers on time, while reducing miles driven and carbon emissions from fuel,” Qualizza says. “That is the essence of CONDOR; it revisits all those decisions and finds those opportunities for us to further delight customers.”

Related content

DE, Berlin
AWS AI is looking for passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Conversational AI Systems. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), Dialog Systems including Generative AI with Large Language Models (LLMs) and Applied Machine Learning (ML). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use language technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are hiring in all areas of human language technology and code generation. We are open to hiring candidates to work out of one of the following locations: Berlin, DEU
US, MA, North Reading
Working at Amazon Robotics Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart, collaborative team of doers that work passionately to apply cutting-edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Position Overview The Amazon Robotics (AR) Software Research and Science team builds and runs simulation experiments and delivers analyses that are central to understanding the performance of the entire AR system. This includes operational and software scaling characteristics, bottlenecks, and robustness to “chaos monkey” stresses -- we inform critical engineering and business decisions about Amazon’s approach to robotic fulfillment. We are seeking an enthusiastic Data Scientist to design and implement state-of-the-art solutions for never-before-solved problems. The DS will collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the Customer experience. They will partner with technology and product leaders to solve business problems using scientific approaches. They will build new tools and invent business insights that surprise and delight our customers. They will work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes. They will work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors. They will engage with software development teams and warehouse design engineers to drive the evolution of the AR system, as well as the simulation engine that supports our work. Inclusive Team Culture Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 87,000 employees across hundreds of chapters around the world. We have innovative benefit offerings and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust. Flexibility It isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth We care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! We are open to hiring candidates to work out of one of the following locations: North Reading, MA, USA
CN, Shanghai
亚马逊云科技上海人工智能实验室OpenSearch 研发团队正在招募应用科学实习生-多模态检索与生成方向实习生。OpenSearch是一个开源的搜索和数据分析套件, 它旨在为数据密集型应用构建解决方案,内置高性能、开发者友好的工具,并集成了强大的机器学习、数据处理功能,可以为客户提供灵活的数据探索、丰富和可视化功能,帮助客户从复杂的数据中发现有价值的信息。OpenSearch是现有AWS托管服务(AWS OpenSearch)的基础,OpenSearch核心团队负责维护OpenSearch代码库,他们的目标是使OpenSearch安全、高效、可扩展、可扩展并永远开源。 点击下方链接查看申请手册获得更多信息: https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e Key job responsibilities 在这个实习期间,你将有机会: 1. 研究最新的搜索相关性人工智能算法。 2. 探索大模型技术在数据分析与可视化上的应用。 3. 了解主流搜索引擎Lucene的原理和应用。深入了解前沿自然语言处理技术和底层索引性能调优的结合。 4. 学习亚马逊云上的各种云服务。 5. 参与产品需求讨论,提出技术实现方案。 6. 与国内外杰出的开发团队紧密合作,学习代码开发和审查的流程。 We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, Shanghai
亚马逊云科技上海人工智能实验室OpenSearch 研发团队正在招募应用科学家实习,方向是服务器端开发。OpenSearch是一个开源的搜索和数据分析套件, 它旨在为数据密集型应用构建解决方案,内置高性能、开发者友好的工具,并集成了强大的机器学习、数据处理功能,可以为客户提供灵活的数据探索、丰富和可视化功能,帮助客户从复杂的数据中发现有价值的信息。OpenSearch是现有AWS托管服务(AWS OpenSearch)的基础,OpenSearch核心团队负责维护OpenSearch代码库,他们的目标是使OpenSearch安全、高效、可扩展、可扩展并永远开源。 点击下方链接查看申请手册获得更多信息: https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e Key job responsibilities 在这个实习期间,你将有机会: 1. 使用Java/Kotlin等服务器端技术编写高质量,高性能,安全,可维护和可测试的代码。 2. 了解主流搜索引擎Lucene的原理和应用。 3. 学习亚马逊云上的各种云服务。 4. 参与产品需求讨论,提出技术实现方案。 5. 与国内外杰出的开发团队紧密合作,学习代码开发和审查的流程。 6. 应用先进的人工智能和机器学习技术提升用户体验。 We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, Shanghai
亚马逊云科技上海人工智能实验室OpenSearch 研发团队正在招募应用科学家实习,方向是服务器端开发。OpenSearch是一个开源的搜索和数据分析套件, 它旨在为数据密集型应用构建解决方案,内置高性能、开发者友好的工具,并集成了强大的机器学习、数据处理功能,可以为客户提供灵活的数据探索、丰富和可视化功能,帮助客户从复杂的数据中发现有价值的信息。OpenSearch是现有AWS托管服务(AWS OpenSearch)的基础,OpenSearch核心团队负责维护OpenSearch代码库,他们的目标是使OpenSearch安全、高效、可扩展、可扩展并永远开源。 点击下方链接查看申请手册获得更多信息: https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e Key job responsibilities 在这个实习期间,你将有机会: • 使用HTML、CSS和TypeScript/Javascript等前端技术开发用户界面。 • 学习使用Node.js 为用户界面提供服务接口。 • 了解并实践工业级前端产品的开发/部署/安全审查/发布流程。 • 了解并实践前端框架React的使用。 • 参与产品需求讨论,提出技术实现方案。 • 与国内外杰出的开发团队紧密合作,学习代码开发和审查的流程。 • 编写高质量,高性能,安全,可维护和可测试的代码。 • 应用先进的人工智能和机器学习技术提升用户体验。 We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
US, WA, Bellevue
Are you excited about developing generative AI, reinforcement learning and foundation models? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics, we are on a mission to build high-performance autonomous decision systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for an Applied Scientist who will help us build next level simulation and optimization systems with the help of generative AI and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will dive deep into our fulfillment network, understand complex processes and channel your insights to build large scale machine learning models (LLMs, graph neural nets and reinforcement learning) that will be able to understand and optimize the state and future of our buildings, network and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. A day in the life In this role, you will dive deep into our fulfillment network, understand complex processes and channel your insights to build large scale machine learning models (LLMs, graph neural nets and reinforcement learning) that will be able to understand and optimize the state and future of our buildings, network and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
LU, Luxembourg
Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz Pooling Req - JKU Linz We are open to hiring candidates to work out of one of the following locations: Luxembourg, LUX
US, WA, Seattle
Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. Our team leads the science and analytics efforts for the search page and we own multiple aspects of understanding how we can measure customer satisfaction with our experiences. This include building science based insights and novel metrics to define and track customer focused aspects. We are working on a new measurement framework to better quantify and qualify the quality of the search customer experience and are looking for a Senior Applied Scientist to lead the development and implementation of different signals for this framework and tackle new and uncharted territories for search engines using LLMs. Key job responsibilities We are looking for an experienced Sr. Applied Scientist to lead LLM based signals development and data analytics and drive critical product decisions for Amazon Search. In a fast-paced and ambiguous environment, you will perform multiple large, complex, and business critical analyses that will inform product design and business priorities. You will design and build AI based science solutions to allow routine inspection and deep business understanding as the search customer experience is being transformed. Keeping a department-wide view, you will focus on the highest priorities and constantly look for scale and automation, while making technical trade-offs between short term and long-term needs. With your drive to deliver results, you will quickly analyze data and understand the current business challenges to assess the feasibility of different science projects as well as help shape the analytics roadmap of the Science and Analytics team for Search CX. Your desire to learn and be curious will help us look around corners for improvement opportunities and more efficient metrics development. In this role, you will partner with data engineers, business intelligence engineers, product managers, software engineers, economists, and other scientists. A day in the life You are have expertise in Machine learning and statistical models. You are comfortable with a higher degree of ambiguity, knows when and how to be scrappy, build quick prototypes and proofs of concepts, innate ability to see around corners and know what is coming, define a long-term science vision, and relish the idea of solving problems that haven’t been solved at scale. As part of our journey to learn about our data, some opportunities may be a dead end and you will balancing unknowns with delivering results for our customers. Along the way, you’ll learn a ton, have fun and make a positive impact at scale. About the team Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), Earth's most customer-centric company and one of the world's leading internet companies. We provide a highly customer-centric, and team-oriented environment. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, MA, Westborough
The Research Team at Amazon Robotics is seeking a passionate Applied Scientist, with a strong track record of industrial research, innovation leadership, and technology transfer, with a focus on ML Applications. At Amazon Robotics, we apply cutting edge advancements in robotics, software development, Big Data, ML and AI to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We operate hundreds of buildings that employ hundreds of thousands of robots teaming up to perform sophisticated, large-scale missions. There are a lot of exciting opportunities ahead of us that can be unlocked by scientific research. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas. As you could imagine, data is at the heart of our innovation. This role will be participating in creating the ML and AI roadmap, leading science initiatives, and shipping ML products. Key job responsibilities You will be responsible for: - Thinking Big and ideating with Data Science team, other Science teams, and stakeholders across the organization to co-create the ML roadmap. - Collaborating with customers and cross-functional stakeholder teams to help the team identify, disambiguate, and define key problems. - Independently innovating, creating, and iterating ML solutions for given business problems. Especially, using techniques such as Computer Vision, Deep Learning, Causal Inference, etc. - Collaborating with other Science, Tech, Ops, and Business leaders to ship and iterate ML products. - Promoting best practices and mentoring junior team members on problem solving and communication. - Leading state-of-the-art research work and pursuing internal/external scientific publications. A day in the life You will co-create ML/AI roadmap. You will help team identify business opportunities. You will prototype, iterate ML/AI solutions. You will drive communication with stakeholders to implement and ship ML solutions. e.g., computer vision, deep learning, explainable AI, causal inference, reinforcement learning, etc. You will mentor and guide junior team members in delivering projects and business impact. You will work with the team and lead scientific publications. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team You will join a scientifically and demographically diverse research/science team. Our multi-disciplinary team includes scientists with backgrounds in planning/scheduling, grasping/manipulation, machine learning, statistical analysis, and operations research. We develop novel algorithms and machine learning models and apply them to real-word robotic warehouses, including: - Planning/coordinating the paths of thousands of robtos - Dynamic task allocation to thousands of robots. - Learning how to manipulate products sold by Amazon. - Co-designing an optimizing robotic logistics processes. Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. In addition, we coordinate research engagements with academia. We are open to hiring candidates to work out of one of the following locations: Westborough, MA, USA
US, CA, Sunnyvale
Amazon is looking for a passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Machine Translation (MT), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). As part of our AI team in Amazon AGI, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA