Enhancing the Cutting-Edge Algorithm for Vehicle Routing Problems: Scaling New Heights

Enhancing the Cutting-Edge Algorithm for Vehicle Routing Problems: Scaling New Heights

Introduction:

The EURO Meets NeurIPS 2022 Vehicle Routing Competition brought together researchers from operations research (OR) and machine learning (ML) to address challenging vehicle routing problems with time windows (VRPTW) in supply chain logistics. The competition involved solving variants of capacitated VRPTW, including static VRPTW and dynamic VRPTW. The competition attracted 150 teams, and SAS’ Brandon Reese and Yan Xu formed a team called Miles To Go Before We Sleep (MTGBWS). They achieved impressive results, gaining 1st place for static VRPTW in the qualification phase and placing 5th overall in the final phase. The team’s success was attributed to new dispatch heuristics and software engineering techniques that improved solution performance on the competition instances. Through this competition, researchers and practitioners were able to develop and share creative new approaches to solving vehicle routing problems.

Full Article: Enhancing the Cutting-Edge Algorithm for Vehicle Routing Problems: Scaling New Heights

EURO Meets NeurIPS 2022 Vehicle Routing Competition: Bridging Operations Research and Machine Learning

The EURO Meets NeurIPS 2022 Vehicle Routing Competition recently took place, bringing together researchers from the fields of operations research (OR) and machine learning (ML). The competition focused on addressing vehicle routing problems with time windows (VRPTW) and dynamic VRPTW. These problems are crucial in supply chain logistics across various industries, as they involve determining the most efficient routes for a fleet of vehicles to make deliveries.

Traditional Approaches to VRP

Vehicle Routing Problems (VRPs) have long been studied in the field of OR. Traditionally, these problems have been approached by formulating them as optimization problems and finding solutions using exact or heuristic methods. However, as VRPs gain more attention in the machine learning community due to their significance in logistics and supply chain settings, traditional solvers have proven to have high computational costs.

NeurIPS 2022: A Hub for AI and ML Innovations

NeurIPS 2022, one of the most prestigious conferences in the field of AI and machine learning, attracted researchers and practitioners from around the world. It served as a platform for exchanging the latest research ideas and progress in ML, deep learning, and AI. The conference had a hybrid format, with an in-person portion taking place in New Orleans from November 28th to December 3rd, and a virtual portion spanning December 5th to 9th. The EURO Meets NeurIPS 2022 Vehicle Routing Competition was cosponsored by both EURO 2022 and NeurIPS 2022, aiming to inspire novel approaches to improving state-of-the-art techniques in vehicle routing.

Challenges in Vehicle Routing

The competition revolved around solving variants of capacitated VRPTW, where limitations on cargo capacity and time windows for deliveries must be considered. Two variants were particularly focused on: static VRPTW and dynamic VRPTW. In the static VRPTW variant, all delivery requests are known from the start. On the other hand, the dynamic VRPTW variant presents additional challenges by introducing new delivery requests throughout the day, incrementally presented in one-hour blocks called epochs. To solve this variant, it is necessary to predict the most efficient time to serve each delivery request.

Competition Results and Team Performance

The EURO Meets NeurIPS 2022 Vehicle Routing Competition received a positive response from both the OR and ML communities. A total of 150 teams registered, with 50 teams submitting approximately 800 solutions. The team “Miles To Go Before We Sleep” (MTGBWS), consisting of Brandon Reese and Yan Xu from SAS, along with their colleagues Steve Harenberg, Laci Ladanyi, and Rob Pratt, achieved impressive results. In the qualification phase, they secured 1st place for the static VRPTW variant, 13th place for the dynamic VRPTW variant, and 7th place overall. In the final phase, they finished 4th place for the static VRPTW variant, 7th place for the dynamic VRPTW variant, and 5th place overall.

Innovations in Solving VRPs

MTGBWS made significant improvements in two key areas: new dispatch heuristics and software engineering. For the dynamic VRPTW variant, they applied heuristics to determine which delivery requests should be planned for the current epoch and which should be deferred. This involved labeling clients as “must-go” or “optional” based on their time window constraints. Dispatch heuristics, such as the minimum angle heuristic and minimum detour heuristic, helped select the most cost-effective optional clients to include in the route plan.

The team also focused on software engineering practices to identify and address performance bottlenecks in their solver. They augmented the provided baseline implementation with automated benchmarks, profiling tools, and version control. Through rigorous code optimization and refactoring, they were able to improve execution speed, outperforming the baseline solver and most competing teams. Attention to repeatability and rigorous benchmarking ensured the reliability of their algorithm improvements.

Contributing to State-of-the-Art Technology

The EURO Meets NeurIPS 2022 Vehicle Routing Competition presented a unique opportunity for researchers and practitioners to explore new ideas in OR and ML and enhance VRP solver technology. By bringing together two diverse research communities, innovative approaches to a business-critical problem were developed and shared. The success of the MTGBWS team demonstrated the power of leveraging operations research techniques alongside software engineering principles to push the boundaries of current technology. These contributions highlight SAS’s commitment to staying at the forefront of state-of-the-art technology. With their expertise in OR and ML, SAS continues to make valuable contributions to the field of vehicle routing and beyond.

Summary: Enhancing the Cutting-Edge Algorithm for Vehicle Routing Problems: Scaling New Heights

The EURO Meets NeurIPS 2022 Vehicle Routing Competition brought together researchers from operations research (OR) and machine learning (ML) to tackle vehicle routing problems with time windows. Vehicle Routing Problems (VRPs) are crucial in supply chain logistics, and solving them involves finding optimal routes for vehicles to make deliveries. The competition included variants of VRP, such as static and dynamic VRPTW, and attracted participants from around the world. SAS’ Brandon Reese and Yan Xu formed a team called Miles To Go Before We Sleep (MTGBWS), and they achieved impressive results in the competition by employing new dispatch heuristics and software engineering techniques. Their improved solutions showcased the power of OR and ML in enhancing VRP solver technology. The competition served as a platform for researchers and practitioners to share innovative approaches and advancements in the field. SAS’s participation highlighted their commitment to contributing to cutting-edge technology.

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