A Hybrid Ant Lion Optimizer (ALO) Algorithm for Construction Site Layout Optimization

Abstract

A well-planned layout will contribute to saving time and site congestion as well as minimize travel distance, material handling effort, and operational cost. However, most of developed mathematical optimization procedures only work for small-scale problems and often falls into either local or global optima which do not guarantee the further convergence. Therefore, this study is motivated to propose a Hybrid Ant Lion Optimizer (ALO) algorithm inspired by ant lions’ predatory behavior, combining optimization techniques and heuristic methods to overcome a limitation of previous research. The validation has demonstrated that the proposed algorithm is able to provide very competitive results in terms of improved exploration, local optima avoidance, exploitation, and convergence. The hybrid ALO algorithm also finds superior optimal solutions for the majority of site layout problems employed, showing that this algorithm has merits in solving constrained problems with diverse search spaces. The optimal results obtained for the site layout optimization demonstrate the applicability of the proposed algorithm in solving real problems with unknown search spaces as well.

Keywords

• site layout
• optimization
• hybrid ant lion optimizer (alo)
• artificial intelligent