Solving Multiobjective Optimization Problems Using an Artificial Immune System
 Carlos A. Coello Coello,
 Nareli Cruz Cortés
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In this paper, we propose an algorithm based on the clonal selection principle to solve multiobjective optimization problems (either constrained or unconstrained). The proposed approach uses Pareto dominance and feasibility to identify solutions that deserve to be cloned, and uses two types of mutation: uniform mutation is applied to the clones produced and nonuniform mutation is applied to the “not so good” antibodies (which are represented by binary strings that encode the decision variables of the problem to be solved). We also use a secondary (or external) population that stores the nondominated solutions found along the search process. Such secondary population constitutes the elitist mechanism of our approach and it allows it to move towards the true Pareto front of a problem over time. Our approach is compared with three other algorithms that are representative of the stateoftheart in evolutionary multiobjective optimization. For our comparative study, three metrics are adopted and graphical comparisons with respect to the true Pareto front of each problem are also included. Results indicate that the proposed approach is a viable alternative to solve multiobjective optimization problems.
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 Title
 Solving Multiobjective Optimization Problems Using an Artificial Immune System
 Journal

Genetic Programming and Evolvable Machines
Volume 6, Issue 2 , pp 163190
 Cover Date
 20050601
 DOI
 10.1007/s107100056164x
 Print ISSN
 13892576
 Online ISSN
 15737632
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 artificial immune system
 multiobjective optimization
 clonal selection
 Authors

 Carlos A. Coello Coello ^{(1)}
 Nareli Cruz Cortés ^{(1)}
 Author Affiliations

 1. Av. Instituto Politécnico Nacional No. 2508, CINVESTAVIPN, Evolutionary Computation Group, Depto. de Ingeniería Eléctrica, Sección de Computación, Col. San Pedro Zacatenco, México, D. F. 07300, Mexico