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feat(moeo): add real-valued multi-objective local search#87

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evvaletov:feat/moeo-local-search
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feat(moeo): add real-valued multi-objective local search#87
evvaletov wants to merge 3 commits intonojhan:masterfrom
evvaletov:feat/moeo-local-search

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@evvaletov
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@evvaletov evvaletov commented Feb 22, 2026

Summary

Add local search components for real-valued multi-objective optimisation,
enabling hybrid evolutionary + local search strategies.

moeo/src/selection/moeoBestUnvisitedSelect.h — selection operator
that picks unvisited individuals, with optional Pareto-dominance exclusion
filtering.

moeo/src/explorer/moeoRealVectorNeighborhoodExplorer.h — neighborhood
explorer for continuous decision spaces with geometric scaling along
improving directions.

moeo/src/algo/moeoUnifiedDominanceBasedLS_Real.h — archive-based
dominance local search algorithm combining the above components.

moeo/src/moeo — includes for the three new headers.

Dependencies

Once those are merged, this branch can be rebased to drop the dependency
commits.

@nojhan
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nojhan commented Feb 27, 2026

Seems very interesting! I'll review that on a cleaned history.

Eremey Valetov added 3 commits February 28, 2026 19:55
moRealVectorNeighbor: neighbor type for real-valued vector solutions
with delta-based forward/backward moves via moBackableNeighbor.
Add virtual finalize() and hasFinalize() to moeoAlgo/moeoPopAlgo hierarchy.
NSGA-II implements finalize() to recompute fitness and diversity assignments
after population modifications (e.g. immigrant integration in island model).
moeoBestUnvisitedSelect: selects unvisited individuals with optional
Pareto-dominance exclusion filtering.

RealVectorNeighborhoodExplorer: generates random perturbation directions
with geometric scaling along improving directions. Supports per-dimension
epsilon and minimum scaling factors.

moeoUnifiedDominanceBasedLSReal: archive-based dominance local search for
real-valued multi-objective problems.
@evvaletov
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Rebased onto HEAD. This PR includes commits from #83 and #84 as dependencies.

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2 participants