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Inventory management, allocation of human and financial resources, raw material, and energy management are significant challenges for our customers. Operational Research is the answer to these challenges! Our Optiwise solution is a toolbox of optimization technologies to meet your operational challenges.

 

Functionalities

    Use our generic models to address your operational challenges

    A multi-flow model to optimize the structure of a network.

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    A routing model to optimize the route of a fleet of vehicles that must visit several fixed points
  • Rely on OptiWise to :

    Configure and run the optimization models

    Screen Optiwise 2
    Configure an optimization problem taking into account the specificities of your context
  • Rely on OptiWise to :

    Visualize the results of the optimization

    Screen Optiwise 3
    Conduct further analysis and studies

OptiWise in action

Our operations research experts use their in-depth knowledge of optimization algorithms and technologies to adapt OptiWise tools to your context and turn them into powerful decision support tools.

  • DELIVERY PROCESS OPTIMIZATION

    We deployed OptiWise to optimize the delivery process of a major retailer with a network of more than 2,000 stores, 15 warehouses, 120 vehicles, and 3,000 pallets to deliver daily.

    Our client optimized their delivery schedule by 5 minutes: an overall cost reduction of up to 25% and a vehicle fill rate that now reaches 90%.

  • SUPPLY CHAIN RESILIENCE

    OptiWise is used to test the resilience of the supply chain of a major distribution company.

    Thanks to the optimization of networks and delivery routes, a bottom-up modeling of the available processes can be used to simulate different scenarios that impact the client's logistics capacities: loss of warehouse capacity, fleet unavailability, etc.

    OptiWise enables the implementation of relevant responses to these scenarios.

  • COLLECTION NETWORK SIZING

    We deployed OptiWise as part of a prospective study aimed at estimating waste collection schemes throughout the metropolitan area.

    The modeling of the various infrastructures involved (depots, collection sites, etc.) coupled with the scenarios developed by our consultants made it possible to establish the costs and resources to be committed according to the options considered.

    The complete automation of the process made it possible to generate more than a thousand analyses on a set of 1200 collection points in less than 12 hours.

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Our publications

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Boosting search engine capabilities of RegReview:…

RegReview is an AI solution for compliance teams, to automate regulatory monitoring and processes, which brings together several tools, the most essential of which is a search engine operating on a compiled database of custom-built regulatory sources.

The database contains ~300k documents.

2023

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Labeling text clusters with keywords

We propose to explore several keyword extraction techniques to label text clusters obtained after a Text Clustering or a Topic Modeling pipeline. This work is following our previous articles about Topic Modeling and Text Clustering (here and here).

2023

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Synthetic data or how to share sensitive data…

For a period of six months, 5 students from Centrale Supélec and ESSEC worked collaboratively with Sia Partners on building a Python library to create fake - which we'll call synthetic - data.
But what's the point of creating fake data? How could it help organizations?

2023

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