Marine fisheries play an important role in the economic development of Indonesia. Besides being the most affordable source of animal protein in the diet of most people in the country, this industrial sector could provide employment to thousands who live at coastal area. We consider the management of small scale traditional business at North Sumatera Province which processes fish into several local seafood products. The inherent uncertainty of data (for example, demand and fish availability), together with the sequential evolution of data over time leads the production planning problem to be a linear mixed-integer stochastic program. We use a scenario generation based approach for solving the model. The result shows the amount of each fish processed product and the number of workforce needed in each horizon planning. References Birge J. R., Louveaux F. V. Introduction to stochastic programming. New York: Springer; 1997. Mawengkang H., Saib Suwilo, Opim S. Sitompul. Revision Modeling of Two-Stage Stochastic Programming Problem. Journal of Industrial System 2006; 7 (4):6--10. Mawengkang H., Suherman. A Heuristic Method of Scenario Generation in Multi-Stage Decision Problem under Uncertainty. Journal of Industrial System 2007; 8(2) : 98--105. Mulvey J. M., Van derbei R., Zenios S. Robust optimization of large scale systems. Operations research 1995;43 (2): 264--281. Rico-Ramirez V. Two-stage stochastic linear programming: a tutorial. SIAG/OPT Views-and-News 2002; 13 (1): 8--14. Sen S., Higle J. L. Introductory tutorial on stochastic linear programming models. Interfaces 1999; 29 (2): 33--61. Van der Vlerk M. H., Haneveld W. K. Stochastic integer programming: General models and algorithms. Annals of Operations Research,85:39--57,1999.
@article{3020,
title = {Production planning of fish processed product under uncertainty},
journal = {ANZIAM Journal},
volume = {51},
year = {2010},
doi = {10.21914/anziamj.v51i0.3020},
language = {EN},
url = {http://dml.mathdoc.fr/item/3020}
}
Mawengkang, Herman. Production planning of fish processed product under uncertainty. ANZIAM Journal, Tome 51 (2010) . doi : 10.21914/anziamj.v51i0.3020. http://gdmltest.u-ga.fr/item/3020/