TY  - JOUR
SN  - 02786125
PB  - Elsevier B.V.
Y1  - 2013///
VL  - 32
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922001879&doi=10.1016%2fj.jmsy.2012.10.004&partnerID=40&md5=ece68f13ad4a01bb13954f129610e9b9
JF  - Journal of Manufacturing Systems
A1  - Ganesan, T.
A1  - Vasant, P.
A1  - Elamvazuthi, I.
AV  - none
KW  - Economic and social effects; Genetic algorithms; Heuristic algorithms; Heuristic methods; Molds; Particle swarm optimization (PSO)
KW  -  Green sand mould systems; Multi objective; Normal boundary intersections; Pareto frontiers; Uniform spread
KW  -  Multiobjective optimization
ID  - scholars3802
TI  - Normal-boundary intersection based parametric multi-objective optimization of green sand mould system
N2  - 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. © 2012 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
N1  - cited By 22
IS  - 1
ER  -