Authors: Nuno Ricardo Costa; João Lourenço
Addresses: Instituto Politécnico de Setúbal – ESTSetúbal, Campus do IPS, Estefanilha, 2910-761 Setúbal, Portugal; UNIDEMI/DEMI, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal ' Instituto Politécnico de Setúbal – ESTSetúbal, Campus do IPS, Estefanilha, 2910-761 Setúbal, Portugal; INESC-ID, Rua Alves Redol 9, 1000-029 Lisboa, Portugal
Abstract: Methods to solve multi-response problems developed under the RSM framework are rarely evaluated in terms of their ability to depict Pareto frontiers and their solutions do not provide information about response properties. This manuscript contributes for positioning some optimisation methods in relation to each other based on their ability to capture solutions in convex and non-convex surfaces in addition to the robustness, quality of predictions and bias of the generated solutions. Results show that an appealing compromise programming-based method can compete with leading methods in the field. It does not require preference information from the decision-maker, is easy-to-implement, can generate solutions to satisfy decision-makers with different sensitivity to bias and variance based on performance metric values, and evenly distributed solutions along the Pareto frontier. The validity of these results is supported on three examples.
Keywords: multiple response problems; optimisation criteria; bias; compromise programming; preferences; multicriteria; non-convex surfaces; non-dominated solutions; optimal; Pareto; robustness; response surface methodology; RSM; variance.
International Journal of Industrial and Systems Engineering, 2015 Vol.20 No.4, pp.437 - 456
Available online: 19 Jun 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article