Constructive cooperative coevolutionary optimisation for interacting production stations
Journal article, 2015

Optimisation of the control function for multiple automated interacting production stations is a complex problem, even for skilled and experienced operators or process planners. When using mathematical optimisation techniques, it often becomes necessary to use simulation models to represent the problem because of the high complexity (i.e. simulation-based optimisation). Standard optimisation techniques are likely to either exceed the practical time frame or under-perform compared to the manual tuning by the operators or process planners. This paper presents the Constructive cooperative coevolutionary (C-3) algorithm, which objective is to enable effective simulation-based optimisation for the control of automated interacting production stations within a practical time frame. C-3 is inspired by an existing cooperative coevolutionary algorithm. Thereby, it embeds an algorithm that optimises subproblems separately. C-3 also incorporates a novel constructive heuristic to find good initial solutions and thereby expedite the optimisation. In this work, two industrial optimisation problems, involving interaction production stations, with different sizes are used to evaluate C-3. The results illustrate that with C-3, it is possible to optimise these problems within a practical time frame and obtain a better solution compared to manual tuning.

Optimised production technology

Interacting production stations

Metaheuristic optimisation algorithm

Sheet metal press line

Manufacturing automation

Author

E. Glorieux

University West

F. Danielsson

University West

B. Svensson

University West

Bengt Lennartson

Chalmers, Signals and Systems, Systems and control, Automation

International Journal of Advanced Manufacturing Technology

0268-3768 (ISSN) 1433-3015 (eISSN)

Vol. 80 1-4 673-688

Subject Categories

Communication Systems

Robotics

DOI

10.1007/s00170-015-7012-7

More information

Latest update

4/18/2018