Gideon Avigad
Papers
2
Total Citations
14
H-Index
2
About
Gideon Avigad is a researcher whose work lies at the intersection of multi-objective optimization and robotics, with a particular focus on generating robust, diverse solutions for complex engineering problems. His key research areas include evolutionary multi-objective optimization, robust planning, and adaptive design. In his most cited work, "The sequential optimization-constraint multi-objective problem and its applications for robust planning of robot paths" (2007, 9 citations), Avigad introduced a novel approach that moves beyond traditional Pareto optimization by seeking diverse solutions for multi-objective problems. This work has direct applications in robotics, enabling more resilient path planning under uncertainty. His later paper, "Optimization of Adaptation - A Multi-objective Approach for Optimizing Changes to Design Parameters" (2013, 5 citations), further extends these ideas to adaptive systems, where design parameters must be optimized for changing conditions. While his citation counts reflect a focused, niche impact, Avigad’s contributions are notable for their conceptual innovation—bridging the gap between optimization theory and practical, robust engineering design. His work is particularly valuable for researchers in robotics and design optimization seeking to handle real-world variability.
Research Focus
Key Achievements
Top Papers
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