@article{scholars3802,
           title = {Normal-boundary intersection based parametric multi-objective optimization of green sand mould system},
             doi = {10.1016/j.jmsy.2012.10.004},
          number = {1},
            note = {cited By 22},
          volume = {32},
           pages = {197},
       publisher = {Elsevier B.V.},
         journal = {Journal of Manufacturing Systems},
            year = {2013},
        abstract = {In manufacturing engineering optimization, it is often that one encounters scenarios that are multi-objective (where each of the objectives portray different aspects of the problem). Thus, it is crucial for the engineer to have access to multiple solution choices before selecting of the best solution. In this work, a novel approach that merges meta-heuristic algorithms with the Normal Boundary Intersection (NBI) method is introduced. This method then is used generate optimal solution options to the green sand mould system problem. This NBI based method provides a near-uniform spread of the Pareto frontier in which multiple solutions with gradual trade-offs in the objectives are obtained. Some comparative studies were then carried out with the algorithms developed and used in this work and that from some previous work. Analysis on the performance as well as the quality of the solutions produced by the algorithms is presented here. {\^A}{\copyright} 2012 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922001879&doi=10.1016\%2fj.jmsy.2012.10.004&partnerID=40&md5=ece68f13ad4a01bb13954f129610e9b9},
        keywords = {Economic and social effects; Genetic algorithms; Heuristic algorithms; Heuristic methods; Molds; Particle swarm optimization (PSO), Green sand mould systems; Multi objective; Normal boundary intersections; Pareto frontiers; Uniform spread, Multiobjective optimization},
          author = {Ganesan, T. and Vasant, P. and Elamvazuthi, I.},
            issn = {02786125}
}