A multiobjective stochastic production-distribution planning problem in an uncertain environment considering risk and workers productivity
type: Item
instance of: scholarly article
title: A multiobjective stochastic production-distribution planning problem in an uncertain environment considering risk and workers productivity
zbMATH Open document ID: 1213.90107
DOI: 10.1155/2011/406398
author: S. M. J. Mirzapour Al-E-Hashem
author: Armand Baboli
author: Seyed Jafar Sadjadi
author: Mir-Bahador Aryanezhad
published in: Mathematical Problems in Engineering
publication date: 2011-06-07T00:00:00Z
full work available at URL: https://eudml.org/doc/233242
review text: Summary: A multi-objective two stage stochastic programming model is proposed to deal with a multi-period multi-product multi-site production-distribution planning problem for a midterm planning horizon. The presented model involves majority of supply chain cost parameters such as transportation cost, inventory holding cost, shortage cost, production cost. Moreover some respects as lead time, outsourcing, employment, dismissal, workers productivity and training are considered. Due to the uncertain nature of the supply chain, it is assumed that cost parameters and demand fluctuations are random variables and follow from a pre-defined probability distribution. To develop a robust stochastic model, an additional objective functions is added to the traditional production-distribution-planning problem. So, our multi-objective model includes (i) the minimization of the expected total cost of supply chain, (ii) the minimization of the variance of the total cost of supply chain and (iii) the maximization of the workers productivity through training courses that could be held during the planning horizon. Then, the proposed model is solved applying a hybrid algorithm that is a combination of Monte Carlo sampling method, modified \(\epsilon\)-constraint method and L-shaped method. Finally, a numerical example is solved to demonstrate the validity of the model as well as the efficiency of the hybrid algorithm.
Mathematics Subject Classification ID: 90B30
Mathematics Subject Classification ID: 90B70
Mathematics Subject Classification ID: 90B90
Mathematics Subject Classification ID: 90C15
zbMATH DE Number: 5904891
Wikidata QID: Q58693012
describes a project that uses: MOAPPS
MaRDI profile type: Publication
OpenAlex ID: W2090648986
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description: scientific article; zbMATH DE number 5904891