本研究旨在探討當雲端服務決策者收到資訊需求時，如何指派資源給後端的作業平台處理，且考量有限的資源下，極小化買方總執行時間和電腦運算時間與成本，極大化賣方利潤與系統可靠度，於雲端運算之資源管理服務上，考量成本付出與資源使用交易之雲端運算經濟議題。研究主要探討不同角色分工中如何分派資源，利用賽局理論概念進行階層式架構建立，導入Stackelberg均勻概念，轉換為二階規劃數學模式，利用本研究所提出之BLSSO演算法（Bi-level Simplified Swarm Optimization）來求解二階線性規劃問題與二階非線性規劃問題。並且將實驗結果與其他啟發式演算法比較，經由測試結果得知，BLSSO演算法具有效率性與品質。

Cloud computing is a configurable resource model “that can be rapidly provisioned and released with minimal management effort or service provider interaction” (NIST). In cloud computing services, buyers and sellers always have strong (leader) or weak (follower) influence, and leaders have the authority to make decisions. Considering how to only reduce the buyer's cost or increase the seller's profit does not reflect the economic situation in reality; therefore, we propose applying the Stackelberg leadership model to the hierarchical structure in cloud computing. Bi-level programming (BLP) can be used to model non-cooperative decision systems, and we propose combining BLP with a simplified swarm optimization (SSO) technique that we call Bi-level Simplified Swarm Optimization (BLSSO) to solve the decision problem. This algorithm uses a dynamic regional search and guarantees global convergence. Computational results show that the proposed BLSSO technique is very competitive and satisfies a number of criteria, including the number of times the best solution is found, average number of the earliest best solution found, and total computational time.

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