Home services are the provision of providing services to people at their homes, e.g., home health care, home beauty care, banking service, appliance repair service, and more. The home service industry, especially home healthcare, has been rapidly growing worldwide due to emergent changes in family structures, work obligations, aging populations, and outspread of chronic and infectious diseases. In 2018, the global home service market was valued at ∼ $282 Billion and is expected to grow by 18.91% annually from 2019-2026, reaching $1,133.4 Billion by 2026 (Verified Market Research, 2019 ). Accordingly, the development of computationally efficient and implementable tools is essential to support decision-making in all areas of the home service industry.
Home services require professional service teams (or one operator) to travel for delivering the services to geographically distributed customers. Service providers often quote an appointment time (planned service start time) to each customer in advance to avoid delivery failure. Therefore, when home service providers plan for service, they need to decide: how many service teams to hire (i.e., sizing problem), how to assign service teams to the customers (i.e., an assignment problem), how to route service teams (i.e., a vehicle routing problem), and how to assign appointment times for the customers (i.e., appointment scheduling problem). This competition aims to address these specific critical operational decision problems in home service. Stochasticity is an intrinsic property of the home service assignment, routing, and appointment scheduling (H-SARA) problem. Here, we will focus on solving H-SARA under three key random factors: service duration, travel time, and customer cancellation. Your team’s goal is to develop an efficient and implementable method to solve H-SARA, which will be used by home service providers.
 Verified Market Research. Global home services market by deployment, by geographic scope and forecast to 2026., Published Date: April 2019.
See the full problem description for more information.
Problem description: MOPTA2021_Competition.pdf
The Finalists have been chosen!
Competition results for the best solution as determined by competition judges:
Winner Team: SolvED (UK)
Institution: University of Edinburgh
Members: Shunee Johnn, Yiran Zhu, Andrés Miniguano-Trujillo
Advisor: Akshay Gupte
Second Place Team: The Optimistics (Colombia)
Institution: Universidad de los Andes
Members: Daniel Yamin, Daniel Barahona
Advisor: Alfaima Solano
Third Place Team: Flamerunners (USA)
Institution: Brown University
Members: Enrique Areyan Viqueira, Shamay Samuel
Advisor: Serdar Kadioglu
You have to register here: registration
You are free to use any software of your choice, but it is recommended to use AIMMS for your submission. All source code must be included, properly documented, and results must be reproducible. AIMMS is an industry-leading rapid model building and deployment platform perfected for over 30 years. AIMMS provides an enjoyable and robust way to not only build optimization models but to deploy them as optimization applications to be used by business professionals. You can develop analytical models and highly interactive end-user interfaces all within the same AIMMS environment.Your team can obtain AIMMS software and request the free academic license from this link.
All files should be submitted as by the deadline a single email with a single attached zip file to . Please start your submission email's subject line with [MOPTA Competition 2021]. The body of the email should forward the registration confirmation email received at registration time, as the way to authenticate the submitting team. Good luck!
Teams of at most three students can participate. The team leader must be a graduate student, though the other members of the team can be advanced undergraduate students. Each member of the team must be registered as a full-time student at a recognized educational institution during the Spring term of the 2020-2021 Academic Year. Students with any background are eligible. Collaboration between students from different departments is strongly encouraged.
Each team must declare a team advisor with which the team may consult about the problem and their solution. It is the team advisor’s responsibility to ensure that the students have appropriate knowledge for the competition. The team advisor should not be involved as a participant in the solution process.
As the conference is international, so is the competition. Teams from all over the world can participate, as long as at least one team member can come to the conference, should the team make it to the final round.
The official language of the competition is English.
Teams are asked to register to the competition as soon as they start working on the problem. There is a separate deadline for the submission of the solution (see Important dates).
If you have questions about the problem or the competition format in general, please contact Dr. Karmel Shehadeh at . If you have questions about the AIMMS software and licensing related issues, please contact .