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Smart Logistics applies simheuristics technology, a family of hybrid algorithms that combine simulation with metaheuristic techniques to solve efficiently complex problems in decision-making under conditions of uncertainty.

With the integration of the large optimization capacity of metaheuristic algorithms and the flexibility of simulation, a very powerful, flexible and relatively easily  implemented methodology is achieved, which, after proper synchronization, can generate pseudo-optimum solutions for real-life applications and for large-scale problems in scenarios of uncertainty.

The type of algorithms generated using this technology is especially suitable for small and medium-sized enterprises (SME), that cannot afford a department to manage decision-taking in logistics and transport, providing them with a powerful tool to enable them to be more competitive in the market.

In the field of smart cities the technology would be suited to all businesses that provide operations and maintenance services, transport services, etc. in towns and cities.

The application of the technology allows solutions to be obtained that provide:

  • a reduction in process times and, consequently, 
  • a reduction in costs.

In the specific field of smart cities, optimization also entails:

  • a reduction in public spending (redistributing the saving in other items in the municipal budget),
  • environmental improvement (atmospheric pollution, noise pollution, etc.),
  • an improvement in the management of spaces (car parks, etc.),
  • a reduction in traffic, etc.

This technology can be applied to any industry where there is a need for process optimization with the aim of obtaining cost reductions (monetary, environmental, etc.). Examples of areas in which it can be rolled out are: logistics, transport, production, finances, telecommunication, mobility and smart cities.

If we look at the field of smart cities, Smart Logistics can be applied to urban solid waste collection management. The technology, in combination with various traceability and measuring devices, enables a dynamic waste collection focus to be developed. Having real-time information about the replacement levels of dumpsters can be used to optimize waste management planning and therefore improve loading and unloading times, with the subsequent translation into a reduction of the associated costs , environmental impact, traffic levels, etc.

Other areas that could benefit from the technology in the field of smart cities are: urban mobility planning, dynamic traffic management, public transport planning, car park management dynamics, etc.

Collaboration with SMATSA for the optimization of waste collection lorry routes. 

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