Applying an Immune Ant Colony System Algorithm to Solve Unequal Area Facility Layout Problem

應用免疫蟻群系統演算法求解部門大小不一致設施規畫問題

張美香(Mei-Shiang Chang)；林欣怡(Hsin-Yi Lin)

蟻群系統 ； 克隆選擇演算法 ； 彈性區帶架構 ； ant colony system ； clonal selection algorithm ； flexible bay structure

先進工程學刊

9卷3期（2014 / 07 / 01）

169 - 175

英文

本研究採用彈性區帶架構，結合克隆選擇演算法及蟻群系統演算法，提出一免疫蟻群系統演算法求解部門大小不一致設施規畫問題。克隆選擇演算法機制的導入可以改善蟻群系統演算法之收斂速度及增加蟻群解間的差異性，故可強化免疫蟻群系統演算法之搜尋能力。將免疫蟻群系統演算法應用於九種標竿問題求解，並與其他研究比較，證實本演算法的搜尋機制可以更快求得最佳的解答。

In this research, the clonal selection algorithm and an ant colony system are combined to propose an immune ant colony system algorithm to solve unequal-area facility layout problems using a flexible bay structure representation. Clonal selection algorithm operations are introduced in the ant colony system to improve the convergence speed of the ant colony system and increase the differences among ant solutions. The search capability of the immune ant colony system is thus enhanced. Datasets for well-known benchmark problems were used to evaluate the effectiveness of this approach. Compared with previous research efforts, the immune ant colony system can offer better solutions in a shorter timeframe for most benchmark problems.