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A GPU accelerated variant of Schroeppel-Shamir's algorithm for solving the market split problem

Please always quote using this URN: urn:nbn:de:0297-zib-100554
  • The market split problem (MSP), introduced by Cornuéjols and Dawande (1998), is a challenging binary optimization problem that performs poorly on state-of-the-art linear programming-based branch-and-cut solvers. We present a novel algorithm for solving the feasibility version of this problem, derived from Schroeppel–Shamir's algorithm for the one-dimensional subset sum problem. Our approach is based on exhaustively enumerating one-dimensional solutions of MSP and utilizing GPUs to evaluate candidate solutions across the entire problem. The resulting hybrid CPU-GPU implementation efficiently solves instances with up to 10 constraints and 90 variables. We demonstrate the algorithm's performance on benchmark problems, solving instances of size (9, 80) in less than fifteen minutes and (10, 90) in up to one day.

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Metadaten
Author:Nils-Christian KempkeORCiD, Thorsten KochORCiD
Document Type:ZIB-Report
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Date of first Publication:2025/07/08
Series (Serial Number):ZIB-Report (25-10)
ISSN:1438-0064
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