Metaheuristics for the Minimum Gap Graph Partitioning Problem
نویسندگان
چکیده
The Minimum Gap Graph Partitioning Problem (MGGPP) consists in partitioning a vertex-weighted undirected graph into given number of connected subgraphs with the minimum difference between largest and smallest weight each subgraph. We propose two-level Tabu Search algorithm an Adaptive Large Neighborhood to solve MGGPP reasonable time on instances up about 23 000 vertices. quality heuristic solutions is assessed comparing them polynomially solvable combinatorial relaxation.
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ژورنال
عنوان ژورنال: Computers & Operations Research
سال: 2021
ISSN: ['0305-0548', '1873-765X']
DOI: https://doi.org/10.1016/j.cor.2021.105301