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In this article, we propose a novel and effective evolutionary algorithm for the challenging combinatorial optimization problem known as Multidimensional Two-Way Number Partitioning Problem (MDTWNPP). Since the MDTWNPP has been proven to be NP-hard, in the recent years, it has been increasingly addressed by means of meta-heuristic approaches. Nevertheless, previous proposals in literature do not make full use of critical problem information that may improve the effectiveness of the search. Here, we bridge this gap by designing an improved Memetic Algebraic Differential Evolution (iMADEB) algorithm that incorporates critical information about the problem. In particular, iMADEB evolves a population of candidate local optimal solutions by adopting three key design concepts: a novel non-redundant bit-string representation which maps population individuals one-to-one to MDTWNPP solutions, a …