How to cite this paper
Chakrabortty, R & Hasin, M. (2013). Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach.International Journal of Industrial Engineering Computations , 4(1), 1-12.
Refrences
Aliev, R.A., Fazlollahi, B., Guirimov, B.G., & Aliev, R.R. (2007). Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management. Information Sciences, 177, 4241– 4255.
Baykasoglu, A. (2001). MOAPPS 1.0: Aggregate production planning using the multiple- objective tabu search. International Journal of Production Research, 39, 3685–3702.
Bellman, R.E., & Zadeh, L.A. (1970). Decision-making in a fuzzy environment. Management Science,
17, 141–164.
Buckley, J.J. (1988). Possibilistic linear programming with triangular fuzzy numbers. Fuzzy Sets and Systems, 26, 135–138.
Buckley, J.J. (1989). Solving possibilistic linear programming problems. Fuzzy Sets and Systems, 31, 329–341.
Bunnag, D., & Sun, M. (2005). Genetic algorithm for constrained global optimization in continuous variables. Applied Mathematics and Computation, 171, 604–636.
Cai, Z., & Wang, Y. (2006). A Multi-objective Optimization-Based Evolutionary Algorithm for Constrained Optimization. IEEE Transactions on Evolutionary Computation, 10 (6), 658-675.
Dobos, I. (2003). Optimal production–inventory strategies for a HMMS-type reverse logistics system. International Journal of Production Economics, 81–82, 351–360.
Fung, R.Y.K., Tang, J., & Wang, D. (2003). Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 33 (3), 302–313.
Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization & Machine Learning. Pearson Education Pvt. Ltd., Singapore.
Gnoni, M.G., Iavagnilio, R., Mossa, G., Mummolo, G., & Leva, A.D. (2003). Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry.
International Journal of Production Economics, 85 (2), 251–262.
Holt, C.C., Modigliani, F., & Simon, H.A. (1955). Linear decision rule for production and employment scheduling. Management Science, 2, 1–30.
Hsu, H.M., & Wang, W.P. (2001). Possibilistic programming in production planning of assemble-toorder environments. Fuzzy Sets and Systems, 119, 59–70.
Hussein, M.L. (1998). Complete solutions of multiple objective transportation problems with possibilistic coefficients. Fuzzy Sets and Systems, 93, 293–299.
Hwang, C.L. & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer, Berlin.
Ioannis, G.T. (2009). Solving constrained optimization problems using a novel genetic algorithm. Applied Mathematics and Computation, 208, 273–283.
Inuiguchi, M., & Sakawa, M. (1996). Possible and necessary efficiency in possibilistic multiobjective linear programming problems and possible efficiency test. Fuzzy Sets and Systems, 78, 231–241.
Jensen, H.A., & Maturana, S. (2002). A possibilistics decision support system for imprecise mathematical programming problems. International Journal of Production Economics, 77 (2), 145– 158.
Lai, Y.J. and Hwang, C.L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49, 121–133.
Lee, Y.Y. (1990). Fuzzy set theory approach to aggregate production planning and inventory control. Ph.D. Dissertation, Department of I.E., Kansas State University.
Masud, S.M., & Hwang, C.L. (1980). An aggregate production planning model and application of three
multiple objective decision methods. International Journal of Production Research, 18, 741–752.
Moghaddam, R.T., & Safaei, N. (2006). Solving a generalized aggregate production planning problem
by genetic algorithms. Journal of Industrial Engineering International, 2(1), 53-64.
Ramezanian, R., Rahmani, D., & Barzinpour, F. (2012). An aggregate production planning model for
two phase production systems: Solving with genetic algorithm and tabu search. Expert Systems with
Applications, 39, 1256-1263.
Saad, G. (1982). An overview of production planning model: Structure classification and empirical assessment. International Journal of Production Research, 20, 105–114.
Schaffer, J.D. (1985). Multiple objective optimization with vector evaluated genetic algorithms. Proceedings of an International Conference on Genetic Algorithms and Their Applications, 93-100.
Sharma, D.K., & Jana, R.K. (2009). Fuzzy goal programming based genetic algorithm approach to nutrient management for rice crop planning. International Journal of Production Economics, 121,224–232.
Summanwar, V.S., Jayaraman, V.K., Kulkarni, B.D., Kusumakar, H.S., Gupta, K., & Rajesh, J. (2002).
Solution of constrained optimization problems by multi-objective genetic algorithm. Computers and Chemical Engineering, 26, 1481–1492.
Wang, R.C., & Fang, H.H. (2001). Aggregate production planning with multiple objectives in a fuzzy environment. European Journal of Operational Research, 133, 521–536.
Wang, R.C., & Liang, T.F. (2004). Application of fuzzy multi-objective linear programming to aggregate production planning. Computers and Industrial Engineering, 46 (1), 17–41.
Wang, R.C., & Liang, T.F. (2005). Applying possibilistic linear programming to aggregate production planning. International Journal of Production Economics, 98, 328-341.
Yeh, W.C., & Chuang, M.C. (2011). Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Systems with Applications, 38, 4244-4253.
Zadeh, L.A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3–28.
Zimmermann, H.J. (1976). Description and optimization of fuzzy systems. International Journal of General Systems, 2, 209–215.
Zimmermann, H.J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1, 45–56.
Baykasoglu, A. (2001). MOAPPS 1.0: Aggregate production planning using the multiple- objective tabu search. International Journal of Production Research, 39, 3685–3702.
Bellman, R.E., & Zadeh, L.A. (1970). Decision-making in a fuzzy environment. Management Science,
17, 141–164.
Buckley, J.J. (1988). Possibilistic linear programming with triangular fuzzy numbers. Fuzzy Sets and Systems, 26, 135–138.
Buckley, J.J. (1989). Solving possibilistic linear programming problems. Fuzzy Sets and Systems, 31, 329–341.
Bunnag, D., & Sun, M. (2005). Genetic algorithm for constrained global optimization in continuous variables. Applied Mathematics and Computation, 171, 604–636.
Cai, Z., & Wang, Y. (2006). A Multi-objective Optimization-Based Evolutionary Algorithm for Constrained Optimization. IEEE Transactions on Evolutionary Computation, 10 (6), 658-675.
Dobos, I. (2003). Optimal production–inventory strategies for a HMMS-type reverse logistics system. International Journal of Production Economics, 81–82, 351–360.
Fung, R.Y.K., Tang, J., & Wang, D. (2003). Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 33 (3), 302–313.
Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization & Machine Learning. Pearson Education Pvt. Ltd., Singapore.
Gnoni, M.G., Iavagnilio, R., Mossa, G., Mummolo, G., & Leva, A.D. (2003). Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry.
International Journal of Production Economics, 85 (2), 251–262.
Holt, C.C., Modigliani, F., & Simon, H.A. (1955). Linear decision rule for production and employment scheduling. Management Science, 2, 1–30.
Hsu, H.M., & Wang, W.P. (2001). Possibilistic programming in production planning of assemble-toorder environments. Fuzzy Sets and Systems, 119, 59–70.
Hussein, M.L. (1998). Complete solutions of multiple objective transportation problems with possibilistic coefficients. Fuzzy Sets and Systems, 93, 293–299.
Hwang, C.L. & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer, Berlin.
Ioannis, G.T. (2009). Solving constrained optimization problems using a novel genetic algorithm. Applied Mathematics and Computation, 208, 273–283.
Inuiguchi, M., & Sakawa, M. (1996). Possible and necessary efficiency in possibilistic multiobjective linear programming problems and possible efficiency test. Fuzzy Sets and Systems, 78, 231–241.
Jensen, H.A., & Maturana, S. (2002). A possibilistics decision support system for imprecise mathematical programming problems. International Journal of Production Economics, 77 (2), 145– 158.
Lai, Y.J. and Hwang, C.L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49, 121–133.
Lee, Y.Y. (1990). Fuzzy set theory approach to aggregate production planning and inventory control. Ph.D. Dissertation, Department of I.E., Kansas State University.
Masud, S.M., & Hwang, C.L. (1980). An aggregate production planning model and application of three
multiple objective decision methods. International Journal of Production Research, 18, 741–752.
Moghaddam, R.T., & Safaei, N. (2006). Solving a generalized aggregate production planning problem
by genetic algorithms. Journal of Industrial Engineering International, 2(1), 53-64.
Ramezanian, R., Rahmani, D., & Barzinpour, F. (2012). An aggregate production planning model for
two phase production systems: Solving with genetic algorithm and tabu search. Expert Systems with
Applications, 39, 1256-1263.
Saad, G. (1982). An overview of production planning model: Structure classification and empirical assessment. International Journal of Production Research, 20, 105–114.
Schaffer, J.D. (1985). Multiple objective optimization with vector evaluated genetic algorithms. Proceedings of an International Conference on Genetic Algorithms and Their Applications, 93-100.
Sharma, D.K., & Jana, R.K. (2009). Fuzzy goal programming based genetic algorithm approach to nutrient management for rice crop planning. International Journal of Production Economics, 121,224–232.
Summanwar, V.S., Jayaraman, V.K., Kulkarni, B.D., Kusumakar, H.S., Gupta, K., & Rajesh, J. (2002).
Solution of constrained optimization problems by multi-objective genetic algorithm. Computers and Chemical Engineering, 26, 1481–1492.
Wang, R.C., & Fang, H.H. (2001). Aggregate production planning with multiple objectives in a fuzzy environment. European Journal of Operational Research, 133, 521–536.
Wang, R.C., & Liang, T.F. (2004). Application of fuzzy multi-objective linear programming to aggregate production planning. Computers and Industrial Engineering, 46 (1), 17–41.
Wang, R.C., & Liang, T.F. (2005). Applying possibilistic linear programming to aggregate production planning. International Journal of Production Economics, 98, 328-341.
Yeh, W.C., & Chuang, M.C. (2011). Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Systems with Applications, 38, 4244-4253.
Zadeh, L.A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3–28.
Zimmermann, H.J. (1976). Description and optimization of fuzzy systems. International Journal of General Systems, 2, 209–215.
Zimmermann, H.J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1, 45–56.