The stochastic opportunistic replacement problem, part III: improved bounding procedures
Journal article, 2019

We consider the problem to find a schedule for component replacement in a multi-component system, whose components possess stochastic lives and economic dependencies, such that the expected costs for maintenance during a pre-defined time period are minimized. The problem was considered in Patriksson et al. (Ann Oper Res 224:51–75, 2015), in which a two-stage approximation of the problem was optimized through decomposition (denoted the optimization policy). The current paper improves the effectiveness of the decomposition approach by establishing a tighter bound on the value of the recourse function (i.e., the second stage in the approximation). A general lower bound on the expected maintenance cost is also established. Numerical experiments with 100 simulation scenarios for each of four test instances show that the tighter bound yields a decomposition generating fewer optimality cuts. They also illustrate the quality of the lower bound. Contrary to results presented earlier, an age-based policy performs on par with the optimization policy, although most simple policies perform worse than the optimization policy.

stochastic opportunistic replacement problem

Stochastic programming

maintenace optimization

mixed binary linear optimization

Author

Efraim Laksman

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Ann-Brith Strömberg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Michael Patriksson

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Annals of Operations Research

0254-5330 (ISSN) 1572-9338 (eISSN)

Future Industrial Services Management

VINNOVA, 2014-06-01 -- 2016-08-25.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Computational Mathematics

Transport Systems and Logistics

Other Mathematics

Information Science

Probability Theory and Statistics

Driving Forces

Sustainable development

Areas of Advance

Transport

Production

Energy

Roots

Basic sciences

DOI

10.1007/s10479-019-03278-z

More information

Latest update

10/8/2019