Design and Implementation of an Heuristic-Enhanced Branch-and-Bound
Solver for MILP
- URL: http://arxiv.org/abs/2206.01857v1
- Date: Sat, 4 Jun 2022 00:09:02 GMT
- Title: Design and Implementation of an Heuristic-Enhanced Branch-and-Bound
Solver for MILP
- Authors: Warley Almeida Silva, Federico Bobbio, Flore Caye, Defeng Liu, Justine
Pepin, Carl Perreault-Lafleur, William St-Arnaud
- Abstract summary: We present a solver for Mixed Programs (MIP) developed for the MIP competition.
Given the 10 minutes bound on the computational time established by the rules of the competition, our method focuses on finding a feasible solution.
Our combined methods, when implemented with extensive computational power, can solve 11 of the 19 problems of the training data set.
- Score: 1.03905835096574
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: We present a solver for Mixed Integer Programs (MIP) developed for the MIP
competition 2022. Given the 10 minutes bound on the computational time
established by the rules of the competition, our method focuses on finding a
feasible solution and improves it through a Branch-and-Bound algorithm. Another
rule of the competition allows the use of up to 8 threads. Each thread is given
a different primal heuristic, which has been tuned by hyper-parameters, to find
a feasible solution. In every thread, once a feasible solution is found, we
stop and we use a Branch-and-Bound method, embedded with local search
heuristics, to ameliorate the incumbent solution. The three variants of the
Diving heuristic that we implemented manage to find a feasible solution for 10
instances of the training data set. These heuristics are the best performing
among the heuristics that we implemented. Our Branch-and-Bound algorithm is
effective on a small portion of the training data set, and it manages to find
an incumbent feasible solution for an instance that we could not solve with the
Diving heuristics. Overall, our combined methods, when implemented with
extensive computational power, can solve 11 of the 19 problems of the training
data set within the time limit. Our submission to the MIP competition was
awarded the "Outstanding Student Submission" honorable mention.
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