A TABU SEARCH APPROACH FOR THE BI-OBJECTIVE HOSPITAL SITE DETERMINATION PROBLEM UNDER FUZZY ENVIRONMENT
DOI:
https://doi.org/10.24297/ijct.v16i4.6195Keywords:
Optimization; Fuzzy Bi-Objective transportation problem; Ranking function; Triangular fuzzy number; Optimal solution; Tabu Search.Abstract
The present paper attempts to study the bi-objective hospital site determination problem under fuzzy environment. In this paper, the concept of Tabu search is used for solving bi-objective facility location problem i.e. the most suitable hospital site to be searched out of the various possible sites nearest to the accidental prone areas so as to minimize the total transportation cost along with the transportation time using triangular fuzzy numbers. For this, we first search the hospital sites near accidental prone areas and then on the basis of that we obtain various optimal solutions with different transportation costs and times.
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References
REFERENCES
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xi. Jaeggi, D.M., Parks, G.T., Kipouros, T. and Clarkson, P.J. 2008. The development of a multiobjective Tabu search algorithm for continuous optimisation problems. Eur. J. Oper. Res. 185, 1192–1212.
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xiv. Caballero,R., Gonzalez, M., Guerrero, F. M., Molina, J. and Paralera, C. 2007. Solving a multiobjective location routing problem with a metaheuristic based on Tabu search: application to a real case in Andalusia. European Journal of Operational Research, 177(3), 1751-1763.
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xxvi. Hale, T. S. and Moberg, C. R. 2003. Location science research: a review.Annals of Operations Research, 123(1-4), 21-35.
xxvii. Gupta, A., Kumar, A. and Sharma, M. K. 2012. An algorithm for solving the bi- objective warehouse problem in a fuzzy environment using tabu search, Iranian Journal of Fuzzy Systems,9(1), 1-19.
xxviii. Bortolan, G. and Degani, R. 1985. A review of some methods for ranking fuzzy subsets. Fuzzy Sets and Systems, Vol. 15, 1-19.
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xxxi. Salhi, S. 2002. Defining Tabu List Size and Aspiration Criterion with Tabu Search Methods. Computer and Operational Research 29: pp 67-86.
xxxii. Peng, Zebo. 2010. Tabu Search - Basic Principle and Algorithm. Lecture Note Linköping University.
xxxiii. Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Grunert da Fonseca, V. 2003. Performance assessment of multiobjective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation 7(2) 117-132.
xxxiv. Fonseca, C.M., Knowles, J., Thiele, L., Zitzler, E. 2005. A tutorial on the performance assessment of stochastic multiobjective optimizers. An invited talk presented by J. Knowles at EMO 2005, Guanajuato, Mexico.
xxxv. Deb, K. 2001. Multi-objective Optimization using Evolutionary Algorithms. John Wiley, Chichester
i. Bellman, R. E. and Zadeh, L. A. 1970. Decision making in a fuzzy environment. Management Science. 17(4), 141-64.
ii. Glover, F. 1989. Tabu search-part I. ORSA Journal on Computing, 1(3), 190-206.
iii. Glover, F. 1990. Tabu search-part II. ORSA Journal on Computing, 2(1), 4-32.
iv. Cooper, L. 1963. Location-allocation problems. Operations Research, 11(3), 331-343.
v. Zadeh, L. A. 1965. Fuzzy sets. Information and Control, 8(3), 338-353.
vi. Dubois, D. and Parade, H. 1980. Fuzzy Sets and Systems, Academic Press, New York.
vii. Narasimhan, R. 1979. A fuzzy subset characterization of a site-selection problem. Decision Sciences, 10(4), 618-628.
viii. Melo, M. T., Nickel, S. and Saldanha-da-Gama, F. 2009. Facility location and supply chain management-a review. European Journal of Operational Research, 196(2), 401-412.
ix. Farahani, R. Z., SteadieSei, M. And Asgari, N. 2010. Multiple criteria facility location problems: a survey. Applied Mathematical Modelling, 34(7), 1689-1709.
x. Sakawa, M. 1993. Fuzzy sets and interactive multiobjective optimization. Plenum Press, New York.
xi. Jaeggi, D.M., Parks, G.T., Kipouros, T. and Clarkson, P.J. 2008. The development of a multiobjective Tabu search algorithm for continuous optimisation problems. Eur. J. Oper. Res. 185, 1192–1212.
xii. Bhattacharya, U., Rao, J. R. and Tiwari, R. N. 1992. Fuzzy multi-criteria facility location problem. Fuzzy Sets and Systems, 51(3), 277-287.
xiii. Bhattacharya, U., Rao, J. R. and Tiwari, R. N. 1993. Bi-criteria multi facility location problem in Fuzzy environment. Fuzzy Sets and Systems, 56(2), 145-153.
xiv. Caballero,R., Gonzalez, M., Guerrero, F. M., Molina, J. and Paralera, C. 2007. Solving a multiobjective location routing problem with a metaheuristic based on Tabu search: application to a real case in Andalusia. European Journal of Operational Research, 177(3), 1751-1763.
xv. Zimmermann, H. J. 1983. Using Fuzzy Sets in Operational Research. European Journal of Operational Research 13.
xvi. Battiti, R. and Tecchiolli, G. 1994. The reactive Tabu search. ORSA J. Comput. 6, 126–140.
xvii. Battiti, R. and Tecchiolli, G. 1996. The continuous reactive Tabu search: blending combinatorial optimization and stochastic search for global optimization. Ann. Oper. Res. 63, 151–188.
xviii. Crainic, T.G., Gendreau, M., Rousseau, L.M. 2010. Special issuse on Recent advances in metaheuristics. J. Heuristics 16(3), 235–535.
xix. Joshi, N. and Chauhan, S. S. 2013. Solution of Fuzzy Transportation Problem using Improved VAM with Roubast Ranking Technique. International Journal of Computer Applications Volume 8, No. 15.
xx. Darzentas, J. 1987. A discrete location model with fuzzy accessibility measures. Fuzzy Sets and Systems, 23(1), 149-154.
xxi. Chu, T. C. 2002. Facility location selection using fuzzy TOPSIS under group decisions. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(6), 687-702.
xxii. Kahraman, C., Ruan, D. and Dogan, I. 2003. Fuzzy group decision-making for facility location selection. Information Sciences, 157, 135-153.
xxiii. Gen, M. and Syarif, A. 2005. Hybrid genetic algorithm for multi-time period production/ distribution planning.Computers and Industrial Engineering, 48(4), 799-809.
xxiv. Lin, C. K. Y. and Kwok, R. C. W. 2006. Multi-objective metaheuristics for a location-routing Problem with multiple use of vehicles on real data and simulated data. European Journal of Operational Research, 175(3), 1833-1849.
xxv. Uno, T. and Katagiri, H. 2008. Single and multi-objective defensive location problems on a network. European Journal of Operational Research, 188(1), 76-84.
xxvi. Hale, T. S. and Moberg, C. R. 2003. Location science research: a review.Annals of Operations Research, 123(1-4), 21-35.
xxvii. Gupta, A., Kumar, A. and Sharma, M. K. 2012. An algorithm for solving the bi- objective warehouse problem in a fuzzy environment using tabu search, Iranian Journal of Fuzzy Systems,9(1), 1-19.
xxviii. Bortolan, G. and Degani, R. 1985. A review of some methods for ranking fuzzy subsets. Fuzzy Sets and Systems, Vol. 15, 1-19.
xxix. Li., D. F. 2010. A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to madm problems. Computer and Mathematics with Applications, 60, 1557-1570.
xxx. Akyar, E., Akyar, H. and Duzce, S. A. 2012. A new method for ranking triangular fuzzy numbers. International Journal of Uncertainty, Fuzziness and Knowledge-based systems, Vol 20 (5), 729-740.
xxxi. Salhi, S. 2002. Defining Tabu List Size and Aspiration Criterion with Tabu Search Methods. Computer and Operational Research 29: pp 67-86.
xxxii. Peng, Zebo. 2010. Tabu Search - Basic Principle and Algorithm. Lecture Note Linköping University.
xxxiii. Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Grunert da Fonseca, V. 2003. Performance assessment of multiobjective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation 7(2) 117-132.
xxxiv. Fonseca, C.M., Knowles, J., Thiele, L., Zitzler, E. 2005. A tutorial on the performance assessment of stochastic multiobjective optimizers. An invited talk presented by J. Knowles at EMO 2005, Guanajuato, Mexico.
xxxv. Deb, K. 2001. Multi-objective Optimization using Evolutionary Algorithms. John Wiley, Chichester
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Published
2017-06-20
How to Cite
Joshi, N., Chauhan, S. S. ., & Raja, R. (2017). A TABU SEARCH APPROACH FOR THE BI-OBJECTIVE HOSPITAL SITE DETERMINATION PROBLEM UNDER FUZZY ENVIRONMENT. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 16(4), 6276–6288. https://doi.org/10.24297/ijct.v16i4.6195
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