Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

Bio-inspired Computation Technique to Chance Constrained Fuzzy Goal Programming Model for Resource Allocation in Farm Planning

Print
PDF
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 90 - Number 2
Year of Publication: 2014
Authors:
Debjani Chakraborti
10.5120/15546-4167

Debjani Chakraborti. Article: Bio-inspired Computation Technique to Chance Constrained Fuzzy Goal Programming Model for Resource Allocation in Farm Planning. International Journal of Computer Applications 90(2):20-27, March 2014. Full text available. BibTeX

@article{key:article,
	author = {Debjani Chakraborti},
	title = {Article: Bio-inspired Computation Technique to Chance Constrained Fuzzy Goal Programming Model for Resource Allocation in Farm Planning},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {90},
	number = {2},
	pages = {20-27},
	month = {March},
	note = {Full text available}
}

Abstract

This paper describes the efficient use of a Bio-inspired computation technique to fuzzy goal programming (FGP) formulation of land allocation problems having chance constraints for optimal production of different seasonal crops in agricultural system. In the proposed approach, utilization of total cultivable land, different productive resources, achievement of target levels of the production of seasonal crops and expected profit from the farm are fuzzily described. In the model formulation of the problem, the concept of tolerance membership functions in fuzzy sets for measuring the degree of optimality of crops-production by utilizing the productive resources is considered. In the solution process, achievement of the defined membership goals to the highest degree (unity) to the extent possible on the basis of priorities is determined by employing genetic algorithm (GA) scheme in the decision making environment. A case example is considered to demonstrate the approach.

References

  • Romero, C. 1986 A Survey of Generalized Goal Programming, European Journal of Operational Research, Vol. 25, No. 2, 183 – 191.
  • Glen, J. 1987 Mathematical Models in Farm Planning: A Survey, Operations Research, Vol. 35, 641 – 666.
  • Pal, B. B. and Basu. I. 1996 Selection of Appropriate Priority Structure for Optimal Land Allocation in Agricultural Planning through Goal Programming, Indian Journal of Agricultural Economics, Vol. 51, 342 – 354.
  • Zimmermann, H. -J. 1978 Fuzzy Programming and Linear Programming with Several Objective Functions, Fuzzy Sets and Systems, Vol. 1, No. 1, 45–55.
  • Pal, B. B. and Chakraborti D. 2013 Using Genetic Algorithm for Solving Quadratic Bilevel Programming Problems via Fuzzy Goal Programming, International Journal of Applied Management Science, Vol. 5, No. 2, 172-195.
  • Pal, B. B. and Moitra, B. N. 2004 Using fuzzy goal programming for long range production planning in agricultural systems, Indian Journal of Agricultural Economics, Vol. 59, No. 1, 75 – 90.
  • Pal, B. B. , Chakraborti D. and Biswas, P. 2009 A Genetic Algorithm Based Hybrid Goal Programming Approach to Land Allocation Problem for Optimal Cropping Plan in Agricultural System, Proceedings of 4th International Conference on Industrial and Information Systems (ICIIS) 2009, EICS 1-4, 1-6, Published in IEEE Xplore Digital Library.
  • Charnes, A. and Cooper, W. W. 1959 Chance-constrained Programming, Management Science, Vol. 6, 73-79.
  • Feiring, B. R. , Sastri, T and Sim, I. S. M. 1998 A Stochastic Programming Model for Water Resource Planning, Mathematical Computer Modeling, Vol. 27, No. 3, 1-7.
  • Hulsurkar, S. , Biswal, M. P. and Sinha, S. B. 1997 Fuzzy Programming Approach to Multi-objective Stochastic Linear Programming Problems, Fuzzy Sets and Systems, Vol. 88, 173-181.
  • Luhandjula, M. K. 1984 Fuzzy Approaches for Multiple Objective Liaanear Fractional Optimization, Fuzzy Sets and Systems, Vol. 13, No. 1, 11 – 23.
  • Pal, B. B. , Moitra, B. N. and Maulik, U. 2003 A Goal Programming Procedure for Fuzzy Multiobjective Linear Fractional Programming Problems, Fuzzy Sets and Systems, Vol. 139, 395 – 405.
  • Tiwari, R. N. , Dharmar, S. and Rao, J. R. 1987 Fuzzy Goal Programming – an Additive Model, Fuzzy Sets and Systems, Vol. 24, 27-34.
  • Holland, J. H. 1973 Genetic Algorithms and optimal allocation of trial, SIAM Journal of Computing, Vol. 2, No. 2, 88 - 105.
  • Deb, K. 2002 Multi-objective Optimization using Evolutionary Algorithms, John Wiley & Sons Ltd.
  • Govt. of W. B. , India. 2006. District Statistical Hand Book, Nadia, Department of Bureau of Applied Economics and Statistics.
  • Govt. of W. B. , Action Plan for the year 2004–2005 and 2005–2006, Office of the Principal Agricultural Officer, Nadia, India.
  • Basak, R. K. 2000 Soil Testing and Fertilizer Recommendation, Kalyani Publishers, New Delhi.
  • Govt. of W. B. , Department of Agri-irrigation, Office of the Executive Engineer, Krishnanagar, Nadia, India.
  • Zimmermann, H. -J. 1987 Fuzzy Sets, Decision Making and Expert Systems, Kluwer Academic Publisher.
  • Goldberg, D. E. 1989 Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading. MA.