Application of multi-objective probabilistic fractional programming problem in production planning
Berhanu Belay,
Srikumar Acharya and
Rajashree Mishra
International Journal of Operational Research, 2022, vol. 43, issue 1/2, 150-167
Abstract:
This paper presents the application of multi-objective probabilistic fractional programming problem in production planning. The production planning model for a manufacturing company that produce multiple products with a specified period is formulated by considering some of the parameters in the right hand sides of the constraints as random variables following continuous distribution namely gamma distribution. The formulated mathematical model is a multi-objective probabilistic fractional programming problem. In the solution procedure, the deterministic equivalent of the probabilistic programming problem has not been obtained. The analytical method for multi-objective fractional programming problem has also not been applied to solve the proposed model. A stochastic simulation-based genetic algorithm is applied to solve the proposed model directly. A set of Pareto optimal solutions is obtained for the formulated production planning problem.
Keywords: genetic algorithm; multi-objective programming problem; probabilistic programming problem; stochastic simulation; fractional programming; production planning; gamma distribution; Pareto optimal solution. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=121491 (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:ijores:v:43:y:2022:i:1/2:p:150-167
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().