Related papers: On-Orbit Servicing Optimization Framework with Hig…
Optimizing car sharing systems under demand uncertainty is an emerging problem for ensuring profitable and sustainable operations of these services while taking into account quality of service concerns. With the increasing adoption of…
We study routing for on-demand last-mile logistics with two crucial novel features: i) Multiple depots, optimizing where to pick-up every order, ii) Allowing vehicles to perform depot returns prior to being empty, thus adapting their routes…
This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that…
Power distribution in remote communities often depends on off-grid microgrids. In order to address the reliability challenges for these microgrids, we develop a mathematical model for topology design, capacity planning, and operation of…
This work describes the orchestration of a fleet of rotary-wing Unmanned Aerial Vehicles (UAVs) for harvesting prioritized traffic from random distributions of heterogeneous users with Multiple Input Multiple Output (MIMO) capabilities. In…
The rapid deployment of robotics technologies requires dedicated optimization algorithms to manage large fleets of autonomous agents. This paper supports robotic parts-to-picker operations in warehousing by optimizing order-workstation…
Tanker-based distribution systems have been prevalent in developing countries to supply clean and pure water in different regions. To efficiently operate such tanker service systems, a large fleet of tanker trucks are required to transport…
This paper investigates a hybrid compositional approach to optimal mission planning for multi-rotor Unmanned Aerial Vehicles (UAVs). We consider a time critical search and rescue scenario with two quadrotors in a constrained environment.…
This paper considers a Markov decision model for profit maximization of a cloud computing service provider catering to customers submitting jobs with firm real-time random deadlines. Customers are charged on a per-job basis, receiving a…
This paper presents a decentralized, online planning approach for scalable maneuver planning for large constellations. While decentralized, rule-based strategies have facilitated efficient scaling, optimal decision-making algorithms for…
This paper presents a hybrid approach that integrates trajectory optimization (TO) and reinforcement learning (RL) for motion planning and control of free-flying multi-arm robots in on-orbit servicing scenarios. The proposed system…
This study addresses the challenge of efficiently assigning locomotives in large freight rail networks, where operational complexity and power imbalances make cost-effective planning difficult. It presents a strategic optimization framework…
On-Demand Ride-Pooling services have the potential to increase traffic efficiency compared to private vehicle trips by decreasing parking space needed and increasing vehicle occupancy due to higher vehicle utilization and shared trips,…
The tie-line scheduling problem in a multi-area power system seeks to optimize tie-line power flows across areas that are independently operated by different system operators (SOs). In this paper, we leverage the theory of multi-parametric…
A deep-space exploration mission with low-thrust propulsion to rendezvous with multiple asteroids is investigated. Indirect methods, based on the optimal control theory, are implemented to optimize the fuel consumption. The application of…
A novel decentralised trajectory generation algorithm for Multi Agent systems is presented. Multi-robot systems have the capacity to transform lives in a variety of fields. But, trajectory generation for multi-robot systems is still in its…
Freight consolidation has significant potential to reduce transportation costs and mitigate congestion and pollution. An effective load consolidation plan relies on carefully chosen consolidation points to ensure alignment with existing…
The paper develops a novel design optimization framework and associated computational techniques for staged deployment optimization of complex systems under operational uncertainties. It proposes a local scenario discretization method that…
Efficient handover algorithms are essential for highly performing mobile wireless communications. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless,…
Aiming at analyzing performance in cloud computing, some unpredictable perturbations which may lead to performance downgrade are essential factors that should not be neglected. To avoid performance downgrade in cloud computing system, it is…