Online from: 1972
Subject Area: Electrical & Electronic Engineering
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|Title:||Decision making under uncertainty for a class of production systems with serial and parallel operations|
|Author(s):||D. Orski, (Institute of Information Science and Engineering, Wroclaw University of Technology, Wroclaw, Poland), M. Hojda, (Institute of Information Science and Engineering, Wroclaw University of Technology, Wroclaw, Poland)|
|Citation:||D. Orski, M. Hojda, (2008) "Decision making under uncertainty for a class of production systems with serial and parallel operations", Kybernetes, Vol. 37 Iss: 5, pp.677 - 692|
|Keywords:||Cybernetics, Decision support systems, Operations and production management, Resource allocation|
|Article type:||Research paper|
|DOI:||10.1108/03684920810873290 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||This work was supported by the Polish State Committee for Scientific Research under Grant No. 3T11A 031 28 (2005-2007). This paper is an extended and modified version of the paper presented at the XVI International Conference on Systems Science, Wroclaw, Poland, September 4-6, 2007.|
Purpose – The purpose of this paper is to present results concerning resource distribution problems for a class of production systems composed of production operations described by relations with uncertain parameters – for newly considered serial-parallel and parallel-serial structures.
Design/methodology/approach – The resource distribution problems are formulated. For the typical mathematical model of a single production operation, the resource distribution algorithms are derived analytically or, when that is impossible, numerical procedures for finding solutions to distribution problems are suggested.
Findings – The uncertain variables have been proved as a convenient tool for solving specific optimization problems in production management based on relational knowledge representation with unknown parameters.
Originality/value – The paper presents analytical resource distribution and numerical algorithms for determining the optimal resource distribution, which may be applied in knowledge-based management-level decision systems for serial-parallel and parallel-serial structures of production systems.
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