Determination of optimal production rate in stochastic manufacturing systems by simulation optimisation approach

Mansoureh Farzam Rad, Seyed Mojtaba Sajadi and Ali Hosseinzadeh Kashan

International Journal of Industrial and Systems Engineering, 2015, vol. 20, issue 3, 306-322

Abstract: Production planning is one of the most important functions in the process of production and operation management. The production planning should be made under uncertainty and considering these uncertainties will result in more realistic production planning model. Simulation optimisation methods have been proved to be useful for analysis of different system configurations and/or alternative operating procedures for complex logistic or manufacturing systems under uncertainty. The present article suggested a multi-period multi-product production planning model in a stochastic situation. Due to the probability of three problem parameters, including demand rate, process time and also setup time of every product in each period, the simulation optimisation technique was employed. In fact, through simulation, the system response rate (the mathematical expectation of objective) for various numbers of production rates in different periods was determined, and consequently, we approached the optimal response by simulated annealing algorithm. Finally, a numeral exam was presented and solved through the suggested approach.

Keywords: production planning; simulation; optimisation; simulated annealing; stochastic manufacturing systems; uncertainty; demand rate; process time; setup time. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=69916 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:20:y:2015:i:3:p:306-322

Access Statistics for this article

More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().