Abstract
In this paper, we modify the general-purpose heuristic method called extremal optimization. We compare our results with the results of Boettcher and Percus [1]. Then, some multiobjective optimization problems are solved by using methods motivated by the immune system.
Highlights
Multiobjective optimization problems (MOPs) [2] are existing in many situations in nature
Multiobjective (Multicriteria) optimization has its roots in late 19th century welfare economics, in the works of Edge worth and Pareto
We find the points in this set that minimize the second most important objective f2 ( x)
Summary
Multiobjective optimization problems (MOPs) [2] are existing in many situations in nature. Most realistic optimization problems require the simultaneous optimization of more than one objective function. In this case, it is unlikely that the different objectives would be optimized by the same alternative parameter choices. Definition 2 (Pareto optimality) A solution x ∈ Ω is said to be Pareto optimal with respect to Ω iff; there is no y ∈Ω for whic= h v. { } Definition 4 (Pareto optimal front) The Pareto optimal front PF is the set of objective functions values corresponding to the solutions in PS , i.e=. Several methods have been proposed to solve continuous multiobjective optimization problems.
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