REStack is a new public dataset of 12k+ RE discussions from Stack Exchange sites, enriched with 23 LDA-derived topics grouped into six categories and community-derived difficulty metadata.
In: 2021 IEEE Congress on Evolutionary Computation (CEC), pp
5 Pith papers cite this work, alongside 401 external citations. Polarity classification is still indexing.
5
Pith papers citing it
401
external citations · external index
years
2026 5representative citing papers
Introduces an exact forward-labeling DP algorithm for optimal decoding of fixed customer permutations into electric vehicle routes, plus restricted variants, with experiments showing tractability and quality gains over heuristics.
Seeding CMA-ES restarts from nearest-better-clustering basins with per-basin step and population scaling gives the best aggregate composition-function results across CEC 2014/2017/2020/2022 at D≤20.
Cross-benchmark study tests transfer of AS models between BBOB/CEC suites and robotics/UAV problems, identifying generalization failures in realistic settings.
RKO with tailored decoders yields competitive or superior solutions to commercial MIP solvers on constrained portfolio optimization and time-dependent TSP benchmarks.
citing papers explorer
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REStack: A Large-Scale Dataset of Reverse Engineering Discussions from Stack Exchange
REStack is a new public dataset of 12k+ RE discussions from Stack Exchange sites, enriched with 23 LDA-derived topics grouped into six categories and community-derived difficulty metadata.
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Where to Split and When to Charge: Optimal Route Construction from Customer Permutations in Electric Vehicle Routing
Introduces an exact forward-labeling DP algorithm for optimal decoding of fixed customer permutations into electric vehicle routes, plus restricted variants, with experiments showing tractability and quality gains over heuristics.
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MSC-CMA-ES: Structure-Aware Restarts for CMA-ES via Cyclic Nearest-Better Basin Discovery
Seeding CMA-ES restarts from nearest-better-clustering basins with per-basin step and population scaling gives the best aggregate composition-function results across CEC 2014/2017/2020/2022 at D≤20.
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Evaluating Real-World Generalizability of Algorithm Selection Models
Cross-benchmark study tests transfer of AS models between BBOB/CEC suites and robotics/UAV problems, identifying generalization failures in realistic settings.
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Applying a Random-Key Optimizer on Mixed Integer Programs
RKO with tailored decoders yields competitive or superior solutions to commercial MIP solvers on constrained portfolio optimization and time-dependent TSP benchmarks.