In the context of simulation-based optimisation, this paper reviews recent work related to the
role of metaheuristics, matheuristics (combinations of exact optimisation methods with …

Mobility solutions like ride-sharing and carpooling are becoming popular in many urban and
metropolitan areas around the globe. These solutions, however, create many operational …

With the emergence of fog and edge computing, new possibilities arise regarding the data-
driven management of citizens' mobility in smart cities. Internet of Things (IoT) analytics …

Many real-life systems in production and transportation logistics are complex, large-scale,
and stochastic in nature. As a consequence, simheuristic approaches–which integrate …

Modern production systems require multiple manufacturing centers—usually distributed
among different locations—where the outcomes of each center need to be assembled to …

Due to the recent worries about the environment, the transportation companies are
incentivized to use Alternative Fuel Vehicles (AFVs) instead of the conventional ones …

This work proposes a learnheuristic approach (combination of heuristics with machine
learning) to solve an aerial-drone team orienteering problem. The goal is to maximise the …

Many decision-making processes in our society involve NP-hard optimization problems. The
largescale, dynamism, and uncertainty of these problems constrain the potential use of …

Green transportation is becoming relevant in the context of smart cities, where the use of
electric vehicles represents a promising strategy to support sustainability policies. However …

Scheduling aircraft turnarounds at airports requires the coordination of several
organizations, including the airport operator, airlines, and ground service providers. The …