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End the Delays

WEIVI solves the optimal traffic disruption recovery plans for reasoned decision making and recovery implementation.

Train Delays No More Railway Traffic Optimisation

Technology

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Dynamic optimisation of complex systems

WEIVI´s dynamic optimisation of complex systems leverages predictive digital twin technology and enables solving complex problems efficiently. Thus, we can quickly respond to changes and manage continuously changing complex interactions. WEIVI’s technology harnesses scientific computing and mathematical modelling, which is the only efficient way to solve complex dynamic phenomena.

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Dynamic vs. static optimisation – Choose the right technology

In dynamic phenomena a system may change significantly in time while static systems are time-independent. In static optimisation regularities are fixed, making them easily detectable, e.g., by artificial intelligence. Complex interactions within dynamic systems cannot be understood with static methods, and steering the system towards a desired outcome is simply impossible.

In our dynamic optimisation process both true real-time information and deviations from expectations are fed into WeiviEngine which manages the digital twin environment, which enables efficient optimisation and a smooth process.

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Railway Traffic – A Case for dynamic optimisation of complex systems

In railway traffic, e.g., during switch malfunction or commonplace delays WeiviEngine calculates the schedule and track changes, velocity profiles, and new encounters for traffic control in order to minimise delays and multiplicative effects. Traffic can flow smoothly and the railway’s attractiveness as a mode of transportation is enhanced – strengthening sustainability. Dynamic optimisation enables more efficient usage of the already existing railway network, and most importantly, it allows optimisation of railway traffic during serious breakdowns.

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Deep Techpowerhouse

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Unique strategies

Business growth

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Adviсe

What we do

Beyond the Rail. Architecting the Logic of High-Dimensional Complexity

Alia Dannenberg (FT, KTM)

CEO, Hari Seldon -mallintaja