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AutomatedSeating.com

AutomatedSeating.com

Seating Plans Simplified. Automated seating leverages AI and combinatorial optimization to automate seating arrangements,  creating seating plans in seconds! Built on a modern tech stack with Next.js, Supabase, and Google Cloud, and powered by Minizinc and Google-Or-Tools to solve the generated combinatorial optimization problem.

 

Automated Seating's technologies aligns well with problem in Operations Research domains like scheduling optimization and planning. The problem it solves is inherently a problem of allocating resources (seats) in a manner that maximizes satisfaction and meets specific requirements (guest preferences).

Seating Plans Simplified. Automated seating leverages AI and combinatorial optimization to automate seating arrangements,  creating seating plans in seconds! Built on a modern tech stack with Next.js, Supabase, and Google Cloud, and powered by Minizinc and Google-Or-Tools to solve the generated combinatorial optimization problem.

 

Automated Seating's technologies aligns well with problem in Operations Research domains like scheduling optimization and planning. The problem it solves is inherently a problem of allocating resources (seats) in a manner that maximizes satisfaction and meets specific requirements (guest preferences).

  • Domains:■ Scheduling and Planning
    ■ Resources Allocation
    ■ AI and Data
    ■ Combinatorial Optimization
  • Tech Stack:■ Next.js: For a robust and scalable front-end.
    ■ Supabase: backend as a service.
    ■ Google Cloud
    ■ MiniZinc: For modeling and solving optimization problems.

GenOptGPT

GenOptGPT

GenOptGPT, an experimental project developed by iHQ Tech, represents a cutting-edge approach to solving complex constraint satisfaction and combinatorial optimization problems. Leveraging the power of GPT models and MiniZinc, a high-level constraint modeling language, GenOptGPT can automate the translation of intricate problem statements into optimized MiniZinc code. This tool has broad applications across various domains, including logistics, for optimizing supply chain operations; scheduling, for efficiently managing resources and timelines; and urban planning, for optimizing layouts and infrastructure. Its experimental nature underscores iHQ Tech's commitment to pushing the boundaries of AI and optimization, exploring new ways to apply technology in practical, industry-specific challenges.
GenOptGPT, an experimental project developed by iHQ Tech, represents a cutting-edge approach to solving complex constraint satisfaction and combinatorial optimization problems. Leveraging the power of GPT models and MiniZinc, a high-level constraint modeling language, GenOptGPT can automate the translation of intricate problem statements into optimized MiniZinc code. This tool has broad applications across various domains, including logistics, for optimizing supply chain operations; scheduling, for efficiently managing resources and timelines; and urban planning, for optimizing layouts and infrastructure. Its experimental nature underscores iHQ Tech's commitment to pushing the boundaries of AI and optimization, exploring new ways to apply technology in practical, industry-specific challenges.
  • Domains:■ LLM-Powered Applications
    ■ Operations Research
    ■ Scheduling & Resource Management
    ■ Mathematical Modeling
    ■ Combinatorial Optimization
  • Tech Stack:■ GPT Models: For understanding and translating problem statements.
    ■ GPT Actions: Creating actions connected to docker containers deployed on google cloud.
    ■ MiniZinc: For modeling and solving optimization problems.