Statistically Distinct Plans for Multi-Objective Task Assignment

We study the problem of finding statistically distinct plans for stochastic task assignment problems such as online multi-robot pickup and delivery (MRPD) when facing multiple competing objectives. In many real-world settings robot fleets do not only need to fulfil delivery requests, but also have to consider auxiliary objectives such as...

Topology Optimization of Launcher Structures under Multiple Critical Load Cases

The launch vehicle industry is undergoing a major shift as new commercial organizations are staking claim to large market shares with bold technologies. To stay competitive in this new era, launch vehicle companies must develop new technologies to reduce launch costs while serving the growing demand for space accessibility. A possible solution...

Pareto Set Extrapolation method: an efficient solving technique for multi-objective optimization problems

When considering techniques for producing the Pareto front of a <i>Multi-Objective Optimization Problem</i> (MOOP), there exists a trade-off between the effectiveness of the method in obtaining the Pareto front and the computational cost required to achieve that. For a method to be effective, the generated solutions must result in a true...