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Atoptima

Leverage Decision-Making AI at the core of your Supply Chain

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Description

Atoptima provides advanced decision-making AI solutions designed to optimize supply chain operations. Leveraging over 25 years of expertise in mathematical optimization and Operations Research, the platform delivers powerful solvers that integrate intelligence into transportation routing, article packing, warehouse order preparation, and production task scheduling. The primary goal is to help businesses boost operational performance, improve quality of service, and significantly reduce their carbon footprint through smarter planning and resource utilization.

By moving beyond simple digitalization, Atoptima offers sophisticated decision support systems capable of handling complex constraints. Businesses using Atoptima can expect substantial benefits, including notable reductions in logistics costs and greenhouse gas emissions, alongside drastically decreased planning time. The modular nature of its solvers (RouteSolver, PackSolver, PickSolver, PlanSolver) allows for tailored solutions, enabling companies to automate processes, increase productivity, and achieve greater efficiency and sustainability within their supply chain.

Key Features

  • RouteSolver: Optimizes various routing scenarios including multi-trip, multi-echelon, FTL, LTL, and reverse logistics.
  • PackSolver: Performs 3D packing optimization for parceling, palletization, truck, and cargo loading.
  • PickSolver: Manages warehouse operations like order orchestration, batching, picking, and slotting.
  • PlanSolver: Optimizes production planning, lot-sizing, and scheduling.
  • Assembled Solvers: Allows building synergistic solutions by combining different software bricks.
  • Yield Management: Facilitates load balancing, distribution, and flow allocation.
  • Decision-Making AI: Automates complex decision processes for improved efficiency and error reduction.
  • Decarbonization Focus: Optimizes operations to minimize resource use and reduce carbon footprint.

Use Cases

  • Optimizing multi-stop delivery routes for field services.
  • Planning efficient truck loading to maximize space utilization.
  • Scheduling order picking sequences in warehouses.
  • Coordinating production schedules in manufacturing.
  • Reducing fuel consumption and emissions in transportation logistics.
  • Designing efficient supply chain networks.
  • Improving resource allocation for operational tasks.

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