Multiobjective firefly algorithm for continuous optimization

• Published in: Engineering with computers Vol. 29; no. 2; pp. 175 - 184
• Main Author: Yang, Xin-She
• Format: Journal Article
• Language: English
• Published: London Springer-Verlag 01.04.2013; Springer Nature B.V
• Subjects: Algorithms; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Computer Science; Computer-Aided Engineering (CAD; Control; Dealing; Design optimization; Fireflies; Math. Applications in Chemistry; Mathematical analysis; Mathematical and Computational Engineering; Mathematical models; Nonlinearity; Optimization; Original Article; Systems Theory; Multiobjective; Engineering design; Metaheuristic; Global optimization; Algorithm; Firefly algorithm
• ISSN: 0177-0667; 1435-5663
• DOI: 10.1007/s00366-012-0254-1

Design problems in industrial engineering often involve a large number of design variables with multiple objectives, under complex nonlinear constraints. The algorithms for multiobjective problems can be significantly different from the methods for single objective optimization. To find the Pareto front and non-dominated set for a nonlinear multiobjective optimization problem may require significant computing effort, even for seemingly simple problems. Metaheuristic algorithms start to show their advantages in dealing with multiobjective optimization. In this paper, we extend the recently developed firefly algorithm to solve multiobjective optimization problems. We validate the proposed approach using a selected subset of test functions and then apply it to solve design optimization benchmarks. We will discuss our results and provide topics for further research.