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Milk Production Linear Programing

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Milk Production Linear Programing
2011 2nd International Conference on Education and Management Technology IPEDR vol.13 (2011) © (2011) IACSIT Press, Singapore

Optimal Scheduling in a Milk Production Line Based on Mixed Integer Linear Programming
Habibollah Javanmard1,+ , Kianehkandi2
1,+

Assistant professor, Islamic Azad University, Arak Branch, Arak, Iran 2 Islamic Azad university , Arak Branch, Arak, Iran

Abstract - A Mixed Integer Linear Programming (MILP) model is proposed in this paper that targets the optimal production scheduling in a single milk production line. The model takes into account all the standard constraints encountered in production scheduling (material balances, inventory limitations, machinery capacity, labor shifts and manpower restrictions). Furthermore, it considers special features that characterize milk production, which are limitations in production sequencing mainly due to different fat contents and flavors of various products and sequence-dependent setup times and costs. The objective function that is minimized considers all major sources of variable cost that depend on the production schedule, i.e. changeover cost, inventory cost and labor cost. The model is applied to a milk production line of a Sala industry in Iran and the results are presented and discussed. Keywords: Production scheduling; Mixed integer linear programming; Sequence-dependent setups.

1. Introduction
Several restrictions encountered in everyday production complicate the scheduling problem. The available machine time and man hours constitute a significant restriction to the problem. Another issue in the scheduling process is accomplishment of the production targets. There are several possible modes of operation and the choice among them depends on the goal sought, which could be the optimization of production earliness or tardiness or the optimization of the incurring production profit or cost.. There could also be limitations in the production sequence. Technical issues can arise



References: 32 [1] Allahverdi, A., Gupta, J. N. D., & Aldowaisan, T. (1999). A review of scheduling research involving setup considerations. Omega, 27(2),219–239. [2] Nakhla, M. (1995).. International Journal of Operations & Production Management, 15(8), 73–88. [3] Pinto, J. M., & Grossmann, I. E. (1998). Assignment and sequencing models for the scheduling of chemical processes. Annals of Operations Research, 81, 433–466. [4] Kohansal(2007),national congeress of food technology,1-5 [5] Reklaitis, G. V. (2000). Overview of planning and scheduling technologies.Latin American Applied Research, 30(4), 285–293. [6] Schuermann, A. C., & Kannan, N. P. (1977). A production forecasting and planning system for dairy processing. Computers and Industrial Engineering, 2, 153–158. [7] Sullivan, S., & Secrest, S. C. (1985). A simple optimization DSS for Interfaces, 15, 46–53.Philip DOGANIS(2007)journal of food engineering,445-453. 323

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