Choosing efficient meta-heuristics to solve the assembly line balancing problem : A landscape analysis approach

Abstract

It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated. ; CC BY-NC-ND 3.0 Edited by Peter Butala, Edvard Govekar, Rok Vrabič This study is supported by the European Union's Horizon 2020 research and innovation program under grant agreement no. 723711 through the MANUWORK project. ; This study is supported by the European Union's Horizon 2020 research and innovation program under grant agreement no. 723711 through the MANUWORK project