Razavi Hajiagha, S., Hashemi, S., Sadeghi, M. (2019). Hybrid fuzzy-stochastic approach to multi-product, multi-period, and multi-resource master production scheduling problem: Case of a polyethylene pipe and Fitting manufacturer. Scientia Iranica, 26(3), 1809-1823. doi: 10.24200/sci.2018.20329
Seyed Hossein Razavi Hajiagha; Shide Sadat Hashemi; Mohammadreza Sadeghi. "Hybrid fuzzy-stochastic approach to multi-product, multi-period, and multi-resource master production scheduling problem: Case of a polyethylene pipe and Fitting manufacturer". Scientia Iranica, 26, 3, 2019, 1809-1823. doi: 10.24200/sci.2018.20329
Razavi Hajiagha, S., Hashemi, S., Sadeghi, M. (2019). 'Hybrid fuzzy-stochastic approach to multi-product, multi-period, and multi-resource master production scheduling problem: Case of a polyethylene pipe and Fitting manufacturer', Scientia Iranica, 26(3), pp. 1809-1823. doi: 10.24200/sci.2018.20329
Razavi Hajiagha, S., Hashemi, S., Sadeghi, M. Hybrid fuzzy-stochastic approach to multi-product, multi-period, and multi-resource master production scheduling problem: Case of a polyethylene pipe and Fitting manufacturer. Scientia Iranica, 2019; 26(3): 1809-1823. doi: 10.24200/sci.2018.20329
Hybrid fuzzy-stochastic approach to multi-product, multi-period, and multi-resource master production scheduling problem: Case of a polyethylene pipe and Fitting manufacturer
1Department of Management, Khatam University, Tehran, Iran
2Department of Management, Saramadan Andishe Avina Co. Tehran, Iran
3Industrial Management Group, Faculty of Management and Accounting, Allameh Tabatabaei University, Tehran, Iran
Abstract
Master production scheduling is an effective phase of production planning which leads to scheduling and magnitude of different products production in a company. This problem requires investigating a wide range of parameters, regarding demand, manufacturing resource usage and costs. Uncertainty is an intrinsic characteristic of these parameters. In this paper, a model is developed for master production scheduling under uncertainty, in which demands, as time-dependent variables, are considered as stochastic variables, while cost and utilization parameters, with cognitive ambiguity, are expressed as fuzzy numbers. A hybrid approach is also proposed to solve the extended model. The application of the proposed method is examined in a practical problem of a polyethylene pipe and fitting Co. in Iran. The result showed a high degree of applicability.
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