Violation-based, diversity-based via k-medoids, and hybrid Benders cut filtering strategies solve more instances and cut solve times by 55-57% compared to adding all cuts.
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This paper proposes a research agenda for software engineering of self-adaptive robotic systems along lifecycle stages and enabling technologies, identifying challenges and a roadmap to 2030.
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.
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Benders Cut Filtering for Affine Potential-Based Flow Problems with Robustness Scenarios and Topology Switching
Violation-based, diversity-based via k-medoids, and hybrid Benders cut filtering strategies solve more instances and cut solve times by 55-57% compared to adding all cuts.
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Software Engineering for Self-Adaptive Robotics: A Research Agenda
This paper proposes a research agenda for software engineering of self-adaptive robotic systems along lifecycle stages and enabling technologies, identifying challenges and a roadmap to 2030.
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Genetic-based fog colony optimization hybridized with hierarchical clustering and its influence in the placement of fog services
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.