Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Abstract— Finding a path in a network based on multiple constraints (the MCP problem) is often referred to as QoS routing. QoS routing with constraints on multiple additive metri...
We consider the problem of energy minimization for periodic preemptive hard real-time tasks that are scheduled on an identical multiprocessor platform with dynamic voltage scaling...
Recently, genetic algorithms (GAs) and their hybrids have achieved great success in solving difficult combinatorial optimization problems. In this paper, the issues related to the ...