How to cite this paper
Singh, D & Ingole, S. (2019). Multi-objective facility layout problems using BBO, NSBBO and NSGA-II metaheuristic algorithms.International Journal of Industrial Engineering Computations , 10(2), 239-262.
Refrences
Aiello, G., Scalia, G. L. & Enea, M. (2012). A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding. Expert Systems with Applications, 39, 10352–10358.
Aiello, A., LaScalia, G. & Enea, M. (2013). A non-dominated ranking multi objective Genetic Algorithm & electre method for unequal area facility layout problems. Expert Systems with Applications, 40, 4812–4819.
Alroomi, A. R., Albasri, F. A. & Talaq, J. H. (2013). Essential modifications on Biogeography-based optimization algorithm. Computer Science & Information Technology, 141-160. doi: 10.5121/csit.2013.3812
Chen, G. Y. & Lo, J. (2014). Dynamic facility layout with multi-objectives. Asia-pacific Journal of Operation Research, 31(4), 1450027. doi: 10.1142/s0217595914500274
Chen, C.W. & Sha, D.Y. (1999). A design approach to the multi-objective facility layout problem. International journal of production research, 37(5), 1175- 1196.
Chen, C.W. & Sha, D.Y. (2005). Heuristic approach for solving the multi-objective facility layout problem. International Journal of Production Research, 43(21), 4493–4507.
Chiang, W. C., Kouvelis, P. & Urban, T. L. (2006). Single- & multi-objective facility layout with workflow interference considerations. European Journal of Operational Research, 174, 1414–1426.
Chutima, P. & Naruemitwong, W. (2014). A Pareto biogeography-based optimisation for multi-objective two-sided assembly line sequencing problems with a learning effect. Computers & Industrial Engineering, 69, 89–104.
Deb, K., Pratap, A., Agarwal, S. & Meyarivan, T. (2002). A fast & elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 82–197.
Dutta, K. N. & Sahu, S. (1982). A multigoal heuristic for facilities design problems: MUGHAL. International Journal of Production Research, 20(2), 147-154.
Fortenberry, J. C. & Cox, J. F. (1985). Multiple criteria approach to the facilities layout problem. International Journal of Production Research, 23(4), 773–782.
Harmonosky, C. M. & Tothero, G. K., (1992). A multi-factor plant layout methodology. International Journal of Production Research, 30, 1773–1789.
Hathhorn, J., Sisikoglu, H. & Mustafa Y. (2013). A multi-objective mixed-integer programming model for a multi-floor facility layout. International Journal of Production Research, 51(14), 4223–4239.
Jolai, F., Moghaddam, R.T. & Taghipour, M. (2012). A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations. International Journal of Production Research, 50(15), 4279–4293.
Khare, V. K., Khare, M. K. & Neema, M. L. (1988). Combined computer-aided approach for the facilities design problem & estimation of the distribution parameter in the case of multi-goal optimization. Computers & Industrial Engineering, 14(4), 465-476.
Ku, M.Y., Hu, M. H. & Wang, M. J. (2011).Simulated annealing based parallel genetic algorithm for facility layout problem. International Journal of Production Research, 49 (6), 1801–1812.
Lim, W. L., Wibowo, A., Desa, M. I. & Haron, H. (2016). A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem. Computational Intelligence & Neuroscience, Article ID 5803893. doi: org/10.1155/2016/5803893
Ma, H., Ruan, X., & Pan, Z. (2012). H&ling multiple objectives with biogeography-based Optimization. International Journal of Automation & Computing, 9(1), 30-36.
Ma, H., Su, S., Simon, D. & Fei, M. (2015). Ensemble multi-objective biogeography-based optimization with application to automated warehouse scheduling. Engineering Applications of Artificial Intelligence, 44, 79–90.
Matai, R., Singh, S.P. & Mittal, M.L. (2013). Modified simulated annealing based approach for multi objective facility layout problem. International Journal of Production Research, 51(14), 4273–4288.
Matai, R. (2015). Solving multi objective facility layout problem by modified simulated annealing. Applied Mathematics & Computation, 261, 302–311.
Peer, S. K. & Sharma, D. K. (2008). Human–computer interaction design with multi-goal facilities layout model. Computers & Mathematics with Applications, 56, 2164–2174.
Rahmati, S. A. & Zandieh, M. (2012). A new biogeography-based optimization (BBO) algorithm for the flexible job shop scheduling problem. International Journal of Advanced Manufacturing Technology, 58, 1115–1129.
Ripon, K. S. N., Glette, K., Khan, K. N., Hovin, M. & Torresen, J. (2013). Adaptive variable neighbourhood search for solving multi-objective facility layout problems with unequal area facilities. Swarm & Evolutionary Computation, 8, 1–12
Rosenblatt, J. M. (1979). The facilities layout problem: A multi-goal approach. International Journal of Production Research, 17(4), 323–332.
Sahin, R. & Turkbey, O. (2009). A simulated annealing algorithm to find approximate Pareto optimal solutions for the multi-objective facility layout problem. International Journal of Advanced Manufacturing Technology, 41, 1003–1018.
Sahin , R. (2011). A simulated annealing algorithm for solving the bi-objective facility layout problem. Expert Systems with Applications, 38, 4460–4465.
Simon, D. (2008). Biogeography-based optimization. IEEE Transactions on Evolutionary Computation, 12(6), 702-713.
Simon, D. (2013). Evolutionary Optimization Algorithms. John Wiley & Sons, Hoboken, NJ.
Singh, S. P. & Singh, V. K. (2010). An improved heuristic approach for multi-objective facility layout problem. International Journal of Production Research, 48(4), 1171–1194.
Sooncharoen, S., Vitayasak, S., & Pongcharoen, P. (2015). Application of biogeography-based optimisation for machine layout design problem. International Journal of Mechanical Engineering & Robotic Research, 4(3), 251-254.
Urban, T. L. (1987). A multiple criteria model for the facilities layout problem. International Journal of Production Research, 25(12), 1805-1812.
Ye, M., & Zhou, G. (2007). A local genetic approach to multi-objective, facility layout problems with fixed aisles. International Journal of Production Research, 45(22), 5243–5264.
Zhou, X., Liu, Y., Li, B. & Sun, G. (2015). Multi-objective biogeography based optimization algorithm with decomposition for community detection in dynamic networks. Physica A: Statistical Mechanics & its Applications, 436, 430–442.
Aiello, A., LaScalia, G. & Enea, M. (2013). A non-dominated ranking multi objective Genetic Algorithm & electre method for unequal area facility layout problems. Expert Systems with Applications, 40, 4812–4819.
Alroomi, A. R., Albasri, F. A. & Talaq, J. H. (2013). Essential modifications on Biogeography-based optimization algorithm. Computer Science & Information Technology, 141-160. doi: 10.5121/csit.2013.3812
Chen, G. Y. & Lo, J. (2014). Dynamic facility layout with multi-objectives. Asia-pacific Journal of Operation Research, 31(4), 1450027. doi: 10.1142/s0217595914500274
Chen, C.W. & Sha, D.Y. (1999). A design approach to the multi-objective facility layout problem. International journal of production research, 37(5), 1175- 1196.
Chen, C.W. & Sha, D.Y. (2005). Heuristic approach for solving the multi-objective facility layout problem. International Journal of Production Research, 43(21), 4493–4507.
Chiang, W. C., Kouvelis, P. & Urban, T. L. (2006). Single- & multi-objective facility layout with workflow interference considerations. European Journal of Operational Research, 174, 1414–1426.
Chutima, P. & Naruemitwong, W. (2014). A Pareto biogeography-based optimisation for multi-objective two-sided assembly line sequencing problems with a learning effect. Computers & Industrial Engineering, 69, 89–104.
Deb, K., Pratap, A., Agarwal, S. & Meyarivan, T. (2002). A fast & elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 82–197.
Dutta, K. N. & Sahu, S. (1982). A multigoal heuristic for facilities design problems: MUGHAL. International Journal of Production Research, 20(2), 147-154.
Fortenberry, J. C. & Cox, J. F. (1985). Multiple criteria approach to the facilities layout problem. International Journal of Production Research, 23(4), 773–782.
Harmonosky, C. M. & Tothero, G. K., (1992). A multi-factor plant layout methodology. International Journal of Production Research, 30, 1773–1789.
Hathhorn, J., Sisikoglu, H. & Mustafa Y. (2013). A multi-objective mixed-integer programming model for a multi-floor facility layout. International Journal of Production Research, 51(14), 4223–4239.
Jolai, F., Moghaddam, R.T. & Taghipour, M. (2012). A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations. International Journal of Production Research, 50(15), 4279–4293.
Khare, V. K., Khare, M. K. & Neema, M. L. (1988). Combined computer-aided approach for the facilities design problem & estimation of the distribution parameter in the case of multi-goal optimization. Computers & Industrial Engineering, 14(4), 465-476.
Ku, M.Y., Hu, M. H. & Wang, M. J. (2011).Simulated annealing based parallel genetic algorithm for facility layout problem. International Journal of Production Research, 49 (6), 1801–1812.
Lim, W. L., Wibowo, A., Desa, M. I. & Haron, H. (2016). A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem. Computational Intelligence & Neuroscience, Article ID 5803893. doi: org/10.1155/2016/5803893
Ma, H., Ruan, X., & Pan, Z. (2012). H&ling multiple objectives with biogeography-based Optimization. International Journal of Automation & Computing, 9(1), 30-36.
Ma, H., Su, S., Simon, D. & Fei, M. (2015). Ensemble multi-objective biogeography-based optimization with application to automated warehouse scheduling. Engineering Applications of Artificial Intelligence, 44, 79–90.
Matai, R., Singh, S.P. & Mittal, M.L. (2013). Modified simulated annealing based approach for multi objective facility layout problem. International Journal of Production Research, 51(14), 4273–4288.
Matai, R. (2015). Solving multi objective facility layout problem by modified simulated annealing. Applied Mathematics & Computation, 261, 302–311.
Peer, S. K. & Sharma, D. K. (2008). Human–computer interaction design with multi-goal facilities layout model. Computers & Mathematics with Applications, 56, 2164–2174.
Rahmati, S. A. & Zandieh, M. (2012). A new biogeography-based optimization (BBO) algorithm for the flexible job shop scheduling problem. International Journal of Advanced Manufacturing Technology, 58, 1115–1129.
Ripon, K. S. N., Glette, K., Khan, K. N., Hovin, M. & Torresen, J. (2013). Adaptive variable neighbourhood search for solving multi-objective facility layout problems with unequal area facilities. Swarm & Evolutionary Computation, 8, 1–12
Rosenblatt, J. M. (1979). The facilities layout problem: A multi-goal approach. International Journal of Production Research, 17(4), 323–332.
Sahin, R. & Turkbey, O. (2009). A simulated annealing algorithm to find approximate Pareto optimal solutions for the multi-objective facility layout problem. International Journal of Advanced Manufacturing Technology, 41, 1003–1018.
Sahin , R. (2011). A simulated annealing algorithm for solving the bi-objective facility layout problem. Expert Systems with Applications, 38, 4460–4465.
Simon, D. (2008). Biogeography-based optimization. IEEE Transactions on Evolutionary Computation, 12(6), 702-713.
Simon, D. (2013). Evolutionary Optimization Algorithms. John Wiley & Sons, Hoboken, NJ.
Singh, S. P. & Singh, V. K. (2010). An improved heuristic approach for multi-objective facility layout problem. International Journal of Production Research, 48(4), 1171–1194.
Sooncharoen, S., Vitayasak, S., & Pongcharoen, P. (2015). Application of biogeography-based optimisation for machine layout design problem. International Journal of Mechanical Engineering & Robotic Research, 4(3), 251-254.
Urban, T. L. (1987). A multiple criteria model for the facilities layout problem. International Journal of Production Research, 25(12), 1805-1812.
Ye, M., & Zhou, G. (2007). A local genetic approach to multi-objective, facility layout problems with fixed aisles. International Journal of Production Research, 45(22), 5243–5264.
Zhou, X., Liu, Y., Li, B. & Sun, G. (2015). Multi-objective biogeography based optimization algorithm with decomposition for community detection in dynamic networks. Physica A: Statistical Mechanics & its Applications, 436, 430–442.