巨大廢棄物包含廢棄的家具、腳踏車、修剪的樹枝和裝潢廢棄物等。不同種類的巨大廢棄物需要不同的處理流程來處理,主要的處理方式為修繕和拆解、破碎。本研究延用Chang and Wu (2009) 之巨大廢棄物隨機網路設計模式。此外,因為隨機網路設計問題為NP-hard問題,所以本研究發展一啟發式演算法—和聲搜尋法以求解此問題。並利用案例測試此演算法的有效性並且跟基因演算法之求解比較其差異性。在參數分析中,尋找並設定合適的參數,以改善和聲搜尋法的求解速度與求解品質。敏感度分析中,測試不同的參數變化對於隨機網路問題求解的影響。最後,根據本研究的案例測試結果,提出研究的結論與建議。
Bulky waste includes disused furniture, old bicycles, lopping, and waste upholstery etc. Disintegrating, crumbling and repairing are the main disposition of bulky waste. It depends on the kinds of bulky waste to dispose them. This thesis extends the research about the stochastic network design of bulky waste recovery by Chang and Wu (2009). Because this problem is NP-hard, this study develops a meta-heuristic algorithm based on harmony search to solve it. Several numerical examples are utilized to demonstrate the validness of the developed algorithm and to compare with genetic algorithm. The parameter analysis of this harmony search-based algorithm is done to increase the quality and the speed of searching processes. Sensitivity analysis is performed to understand the influence of different parameters on the stochastic network design problem. Finally, some conclusions and suggestions are provided according to the testing results.