A Multi Objective Model For Fish Processed Production Planning Under Uncertainty
||International Journal of Computer Trends and Technology (IJCTT)|
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : Sawaluddin , Herman Mawengkang|
|DOI : 10.14445/22312803/IJCTT-V16P131|
Sawaluddin , Herman Mawengkang. "A Multi Objective Model For Fish Processed Production Planning Under Uncertainty". International Journal of Computer Trends and Technology (IJCTT) V16(4):128-132, Oct 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
In Indonesia one of the very important factor for economic development is marine fisheries. Besides being the most affordable source of animal protein in the diet of most people in the country, this industrial sector could contribute environmental degradation. This paper addresses a multi-objective stochastic programming model of the sustainable production planning of fish processed products. The model takes into account conflicting goals such as return and financial risk and environmental costs. The uncertainty comes from the reliability of financial risk. Starting from it two single objective models are formulated: a maximum expected return model and a minimum financial risk (waste penalties) model. We transform the stochastic programming model into a deterministic optimization model using covariance approach.
 Bevc CA, Marshall BK, Picou JS, “Environmental justice and toxic exposure: toward a spatial model of physical health and psychological well-being,” Soc Sci Res., vol. 36(1), pp. 48–67, 2007.
 Birge JR, Louveaux FV, Introduction to Stochastic Programming, New York: Springer, 1997.
 J.M. Bloemhof-Ruwaard, H. Krikk, and L.N. Van Wassenhove, OR Models for Eco-Eco Closed-Loop Supply Chain Optimization, ser. Reverse Logistics: Quantitative Models for Closed-Loop Supply Chains. 1st ed. Berlin/Heiderberg: Springer-Verlag, 2004, vol 1.
 Giannikos I. “A multi-objective programming model for locating treatment sites and routing hazardous wastes,” Eur J. Operational Res., vol. 104, pp. 333–42, 1998.
 J. Gopal, “The Development of Malaysia’s Palm Oil Refining Industry: Obstacles, Policy, and Performance,” Ph.D Thesis, University of London and Diploma of Imperial College, England, 2001
 G. Huppes and M. Ishikawa, “A framework for quantified eco-efficiency analysis,” Journal of Industrial Ecology, vol. 9(4), pp. 25-41, 2005.
 Jacobs TL and Warmerdam JM, “Simultaneous routing and sitting for hazardous waste operations,” J. Urban Plan Dev., vol. 120(3), pp. 115–31, 1994.
 Jenkins SH and Bassett G, “Perceived risk and uncertainty of nuclear waste,” Risk Anal., vol. 14(5), pp. 851–6, 1994.
 Lindell MK and Earle TC, “How close is close enough: public perceptions of the risks of industrial facilities,” Risk Anal., vol. 3, pp. 245–53, 1983.
 K. Liu and Q. Shyng, “Eco-system in the steel industry,” in Proc. of Inter. Conf. on Cleaner Prod. and Sustainable Development’ 99, Taipei-Taiwan, Dec. 1999.
 McClelland GH, Schulze WD, and Hurd B. “The effect of risk belief on property values: a case study of a hazardous waste site,” Risk Anal., vol. 10(4), pp. 485–97, 1990.
 McCluskey JJ and Rausser GC, “Estimation of perceived risk and its effect on property values,” Land Econ., vol. 77(1), pp. 42–55, 2001.
 ReVelle C, Cohon J, and Shobrys D, “Simultaneous sitting and routing in disposal of hazardous wastes,” Transport Sci., vol. 25(2), pp. 138–45, 1991.
 Sjöberg L, “Determinants and consequences of perceived risk,” in Proceedings of Annual Meeting of the Society for Risk Analysis, 1996.
 R.E. Steuer and C.A. Piercy, “A regression study of the number of efficient extreme points in multiple objective linear programming,” European Journal of Operational Research, vol. 162(2), pp. 484-496, 2005.
 R.E. Steuer, “Random problem generation and the computation of efficient extreme points in multiple objectives linear are programming,” Computational Optimization and Applications, vol. 3, pp. 333-347, 1994.
 S. Prasertsan, C. Bunyakan, and J. Chungsiriporn, “Cleaner production of plam oil milling by process optimization,” PSU-UNS International Conf. On Engineering and Environment – ICEE-2005, Novi Sad, 2005.
 Radulescu M, Radsulescu S, and Radulescu C. Z., “Sustainable production technologies which take into account environmental constraints,” European Journal of Operational Research, vol. 193(3), pp. 730-740, 2009.
 Murugan S, Choo J. K., Sihombing H. 2013 Linear Programming for palm oil industry. Int. Journal of Humanities and Management Sciences (IJHMS), Vol.1, Issue 3, 184-187
Environmental Production Planning, Stochastic Programming, Modelling, Financial risk.