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Main Authors: Shao, Sihong, Wu, Yishan
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2212.06371
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author Shao, Sihong
Wu, Yishan
author_facet Shao, Sihong
Wu, Yishan
contents We propose an ODE approach to solving multiple choice polynomial programming (MCPP) after assuming that the optimum point can be approximated by the expected value of so-called thermal equilibrium as usually did in simulated annealing. The explicit form of the feasible region and the affine property of the objective function are both fully exploited in transforming the MCPP problem into the ODE system. We also show theoretically that a local optimum of the former can be obtained from an equilibrium point of the latter. Numerical experiments on two typical combinatorial problems, MAX-$k$-CUT and the calculation of star discrepancy, demonstrate the validity of our ODE approach, and the resulting approximate solutions are of comparable quality to those obtained by the state-of-the-art heuristic algorithms but with much less cost. This paper also serves as the first attempt to use a continuous algorithm for approximating the star discrepancy.
format Preprint
id arxiv_https___arxiv_org_abs_2212_06371
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle An ODE approach to multiple choice polynomial programming
Shao, Sihong
Wu, Yishan
Optimization and Control
Combinatorics
90C59, 35Q90, 90C09, 90C23
We propose an ODE approach to solving multiple choice polynomial programming (MCPP) after assuming that the optimum point can be approximated by the expected value of so-called thermal equilibrium as usually did in simulated annealing. The explicit form of the feasible region and the affine property of the objective function are both fully exploited in transforming the MCPP problem into the ODE system. We also show theoretically that a local optimum of the former can be obtained from an equilibrium point of the latter. Numerical experiments on two typical combinatorial problems, MAX-$k$-CUT and the calculation of star discrepancy, demonstrate the validity of our ODE approach, and the resulting approximate solutions are of comparable quality to those obtained by the state-of-the-art heuristic algorithms but with much less cost. This paper also serves as the first attempt to use a continuous algorithm for approximating the star discrepancy.
title An ODE approach to multiple choice polynomial programming
topic Optimization and Control
Combinatorics
90C59, 35Q90, 90C09, 90C23
url https://arxiv.org/abs/2212.06371