  This paper proposes and evaluates a Multi-Reference Relaxation Enforced
Neighborhood Search (MRENS) heuristic within the SCIP solver. This study marks
the first integration and evaluation of MRENS in a full-fledged MILP solver,
specifically coupled with the recently-introduced Lagromory separator for
generating multiple reference solutions. Computational experiments on the
MIPLIB 2017 benchmark set show that MRENS, with multiple reference solutions,
improves the solver's ability to find higher-quality feasible solutions
compared to single-reference approaches. This study highlights the potential of
multi-reference heuristics in enhancing primal heuristics in MILP solvers.
