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cs.NE2026
On Scalability of Multi-Objective Evolutionary Algorithms on Combinatorial Optimisation Problems
Menghao Tang, Zimin Liang, Miqing Li
Scalability of evolutionary algorithms refers to assessing how their performance changes as problem size increases. In the area of multi-objective optimisation, research on the sca…
cs.NE2026
Variable Search Stepsize for Randomized Local Search in Multi-Objective Combinatorial Optimization
Xuepeng Ren, Maocai Wang, Guangming Dai +4
Over the past two decades, research in evolutionary multi-objective optimization has predominantly focused on continuous domains, with comparatively limited attention given to mult…
cs.NE2026
Random is Faster than Systematic in Multi-Objective Local Search
Zimin Liang, Miqing Li
Local search is a fundamental method in operations research and combinatorial optimisation. It has been widely applied to a variety of challenging problems, including multi-objecti…