6533b7cffe1ef96bd125833d
RESEARCH PRODUCT
SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization
Manuel LagunaRafael MartíRafael CaballeroJulián Molinasubject
Continuous optimizationNonlinear systemMultiobjective optimization problemMathematical optimizationComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSISGeneral EngineeringEfficient frontierMulti-objective optimizationMetaheuristicGlobal optimizationTabu searchMathematicsdescription
We describe the development and testing of a metaheuristic procedure, based on the scatter-search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of scatter search to multiobjective optimization problems has not been fully explored in the literature. We test the proposed procedure on a suite of problems that have been used extensively in multiobjective optimization. Additional tests are performed on instances that are an extension of those considered classic. The tests indicate that our adaptation of scatter search is a viable alternative for multiobjective optimization.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-02-01 | INFORMS Journal on Computing |