Alternating direction method of multipliers as a simple effective heuristic for mixed-integer nonlinear optimization

被引：0
作者：
Yoshihiro Kanno
Satoshi Kitayama
机构：
[1] The University of Tokyo,Mathematics and Informatics Center
[2] Kanazawa University,Faculty of Mechanical Engineering, Institute of Science and Engineering
来源：
Structural and Multidisciplinary Optimization | 2018年 / 58卷
关键词：
Mixed-integer nonlinear optimization; Nonconvex optimization; Heuristic; Alternating direction method of multipliers;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we propose to utilize a variation of the alternating direction method of multipliers (ADMM) as a simple heuristic for mixed-integer nonlinear optimization problems in structural optimization. Numerical experiments suggest that using multiple restarts of ADMM with random initial points often yields a reasonable solution with small computational cost.
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收藏
页码：1291 / 1295
页数：4
相关论文
共 65 条
  • [1] Ames BPW(2016)Alternating direction method of multipliers for penalized zero-variance discriminant analysis Comput Optim Appl 64 725-754
  • [2] Hong M(2013)Mixed-integer nonlinear optimization Acta Numerica 22 1-131
  • [3] Belotti P(2010)Distributed optimization and statistical learning via the alternating direction method of multipliers Foundations and Trends in Machine Learning 3 1-122
  • [4] Kirches C(1993)Discrete optimization of structures using an improved penalty function method Eng Optim 21 293-306
  • [5] Leyffer S(2012)A storm of feasibility pumps for nonconvex MINLP Math Program, Series B 136 375-402
  • [6] Linderoth J(2018)A general system for heuristic minimization of convex functions over non-convex sets Optimization Methods and Software 33 165-193
  • [7] Luedtke J(2017)Penalty alternating direction methods for mixed-integer optimization: a new view on feasibility pumps SIAM J Optim 27 1611-1636
  • [8] Mahajan A(1999)A regional genetic algorithm for the discrete optimal design of truss structures Int J Numer Methods Eng 44 749-766
  • [9] Boyd S(2004)An improved particle swarm optimizer for mechanical design optimization problems Eng Optim 36 585-605
  • [10] Parikh N(2006)A revised discrete Lagrangian-based search algorithm for the optimal design of skeletal structures using available sections Struct Multidiscip Optim 31 201-210
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