Bat algorithm for multi-objective optimisation

TLDR

Engineering optimisation is typically multi‑objective and multidisciplinary with complex constraints, requiring efficient algorithms, and Xin‑She Yang recently proposed a bat‑inspired algorithm for non‑linear, global optimisation. The paper extends the bat‑inspired algorithm to solve multi‑objective optimisation problems. MOBA is validated on test functions and then applied to multi‑objective design problems such as welded beam design. Simulation results indicate that MOBA works efficiently.

Abstract

Engineering optimisation is typically multi-objective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimisation algorithms. Recently, Xin-She Yang proposed a bat-inspired algorithm for solving non-linear, global optimisation problems. In this paper, we extend this algorithm to solve multi-objective optimisation problems. The proposed multi-objective bat algorithm (MOBA) is first validated against a subset of test functions, and then applied to solve multi-objective design problems such as welded beam design. Simulation results suggest that the proposed algorithm works efficiently.