Tree-Based Optimization: A Meta-Algorithm for Metaheuristic Optimization
It addresses the problem of inefficient global optimization in high-dimensional spaces for fields like integrated circuit design, but appears incremental as it builds on existing metaheuristics.
The paper introduces Tree-Based Optimization (TBO), a meta-algorithm that enhances search performance by iteratively pruning low-fitness parts of the search space using heuristic sub-algorithms, showing improved accuracy and speed, especially in high-dimensional benchmarks like VLSI CAD for IC design.
Designing search algorithms for finding global optima is one of the most active research fields, recently. These algorithms consist of two main categories, i.e., classic mathematical and metaheuristic algorithms. This article proposes a meta-algorithm, Tree-Based Optimization (TBO), which uses other heuristic optimizers as its sub-algorithms in order to improve the performance of search. The proposed algorithm is based on mathematical tree subject and improves performance and speed of search by iteratively removing parts of the search space having low fitness, in order to minimize and purify the search space. The experimental results on several well-known benchmarks show the outperforming performance of TBO algorithm in finding the global solution. Experiments on high dimensional search spaces show significantly better performance when using the TBO algorithm. The proposed algorithm improves the search algorithms in both accuracy and speed aspects, especially for high dimensional searching such as in VLSI CAD tools for Integrated Circuit (IC) design.