On solving multi objective Set Covering Problem with imprecise linear fractional objectives
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 3, pp. 495-510

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The Set Covering problem is one the of most important NP-complete 0-1 integer programming problems because it serves as a model for many real world problems like the crew scheduling problem, facility location problem, vehicle routing etc. In this paper, an algorithm is suggested to solve a multi objective Set Covering problem with fuzzy linear fractional functionals as the objectives. The algorithm obtains the complete set of efficient cover solutions for this problem. It is based on the cutting plane approach, but employs a more generalized and a much deeper form of the Dantzig cut. The fuzziness in the problem lies in the coefficients of the objective functions. In addition, the ordering between two fuzzy numbers is based on the possibility and necessity indices introduced by Dubois and Prade [Ranking fuzzy numbers in the setting of possibility theory. Inf. Sci. 30 (1983) 183–224.]. Our aim is to develop a method which provides the decision maker with a fuzzy solution. An illustrative numerical example is elaborated to clarify the theory and the solution algorithm.

DOI : 10.1051/ro/2014045
Classification : 90C10, 90C70
Keywords: Set covering Problem, multi objective linear fractional programming, fuzzy mathematical programming, fuzzy objective function

Upmanyu, Mudita 1 ; Saxena, Ratnesh R 2

1 Department of Mathematics, University of Delhi, Delhi, India
2 Associate Professor, Department of Mathematics, Deen Dayal Upadhyaya College, University of Delhi, Delhi, India
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     title = {On solving multi objective {Set} {Covering} {Problem} with imprecise linear fractional objectives},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {495--510},
     publisher = {EDP-Sciences},
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Upmanyu, Mudita; Saxena, Ratnesh R. On solving multi objective Set Covering Problem with imprecise linear fractional objectives. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 3, pp. 495-510. doi: 10.1051/ro/2014045

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