Projects in Sustainable Cities

Sustainable Data-Driven Public Transport Systems

Project members:

  • Institute for Computational Intelligence (ICI), Universidad Privada Boliviana
  • Centro de Investigaciones Sociales (CIS), Vicepresidencia del Estado Plurinacional de Bolivia

Project duration: March 2018 – March 2019

Mobility in La Paz is dominated by the so-called informal public transport sector. Transport routes and services are determined by various privately run, often competing syndicates. Vehicles are purchased by individual drivers and the syndicates do not maintain public infrastructure such as bus stops. This results in large fleets of low capacity vehicles competing over passengers and often causing traffic disruptions as well as dangerous traffic conditions. As the population and urban area of La Paz and El Alto are rapidly increasing the organization of the informal transport system increasingly poses a problem to urban development and public health. In this project we seek to analyze the current public transport landscape and to develop intelligent strategies for the improvement of the public transport sector.



Projects in Industry & Innovation

Data-Driven & Emerging Technologies in Supply Chain Management

Project duration: Nov 2018 – ongoing


The Institute for Computational Intelligence, through UPB, is a member of the MIT Global SCALE (Supply Chain and Logistics Excellence) network. With our expertise in computational intelligence we are the regional lead for research projects under the umbrella of “Data-Driven & Emerging Technologies” (DD&ET). As the lead on DD&ET research we are developing research projects and are coordinating collaborations within the Latin American SCALE network.

Read more at: Data-Driven & Emerging Technologies


Demand Forecasting with Recurrent Neural Networks

Project duration: July 2018 – June 2019

In production and operational management demand forecasting is an important method as it helps to develop better approximations of future operations under the presence of uncertainty. Forecasting extracts mathematical relations from past data that can be used to inform future decision making. In supply chain management, efficient coordination of resource acquisition, production and warehousing strongly depends on accurately predicting future product demand in particular and market dynamics in general. Accurate demand forecasting therefore reduces investment risks in uncertain environments. The challenges of demand forecasting lie in the complexity of demand dynamics. We investigate the application of reservoir computing (RC) to product demand forecasting. RC utilizes a randomly initialized recurrent neural network that implements finite memory and generalization. Under these conditions it should be sufficient to reduce training complexity to only a single linear output layer and achieve accurate forecasting results. The output layer is therefore able to derive a simple linear relationship between the input data and its projection into a higher-dimensional feature space.


Slotting Heuristics and Order-picking Efficiency in Warehouse Operations

Project duration: July 2018 – December 2018

Order picking, the process of collecting and sorting a set of products according to customer orders, is the main cost driver in warehouse operations. Order picking consists of travel between product locations, retrieval of the specific stock keeping unit (SKU), and sorting of SKUs according to customer orders. Travel is estimated to contribute approximately 50% of the total order picking costs. Due to daily, weekly, monthly, seasonal and yearly demand fluctuations, order picking efficiency can vary greatly under time-varying order patterns. We investigate the time-dependent dynamics of order picking efficiency in relation to different slotting strategies to understand resilience to order fluctuations and their impact on picking efficiency.




The Political Anatomy of Computer Architecture

Project members:

  • Institute for Computational Intelligence (ICI), Universidad Privada Boliviana
  • Research Laboratory of Communication and Humanities (LIComH), Universidad Privada Boliviana

Project duration: November 2018 – March 2019

Foucault introduced a notion of technology that describes the relationships between social systems, power and mechanisms of control. This is our first link between technology (as method) and power. We reinterpret Foucault’s concepts to describe the functioning of computer architecture. This is our second link between technology (as artifact) and power.

Demonstrating the disciplines and political anatomy on these two distinct systems – one social, one technical – we argue that their similarities are not by chance, but founded in both systems belonging to a more abstract class of large-scale systems composed of homogeneous individuals. In such systems functionality is not derived from characteristics of any particular individual, but from the structure and mechanisms of control homogenized individuals are embedded in and subjected to. Under this assumption we assert that observed organizing principles of the mentioned social and technical systems are inherited from the abstract class.

To derive possible implications we turn to Heidegger’s ideas of Gestell (enframing) and the essence of technology. Starting from our second link between technology and power, we discuss computer architecture as an artifact of modern technology in Heidegger’s sense. Showing how computer architecture exhausts time and uses docile individual transistors to maximize its quantitative output points to Heidegger’s concept of Bestand (standing reserve) and the implicit dangers he saw in it for modern societies.

Extending this thought to our first link between technology and power, the question of the Gestell and the essence of social organization (as technology) arises. Reflecting on shared organizing principles of the mentioned systems we intend to reveal a Gestell of social organization and how its constraints transform humanity into a Bestand. The recognition of political organizing principles outside of social systems can thus lead to a more primal truth of the relations between individuals, structure, functionality and power within large-scale systems.