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Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency) and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.

Mesh router nodes placement is a central problem in Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a Simulated Annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to

Wireless Mesh Networks (WMNs) are an important networking paradigm that offer cost effective Internet connectivity. The performance and operability of WMNs depend, among other factors, on the placement of network nodes in the area. Among the most important objectives in designing a WMN is the formation of a mesh backbone to achieve high user coverage. Given a number of router nodes to deploy, a deployment area and positions of client nodes in the area, an optimization problem can be formulated aiming to find the placement of router nodes so as to maximize network connectivity and user coverage. This optimization problem belongs to facility location problems, which are computationally hard to solve to optimality. In this paper we present the implementation and evaluation of Tabu Search (TS) for the problem of mesh router node placement in WMNs. The experimental evaluation showed the efficiency of TS in solving a benchmark of instances.

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