網格排程問題是一種協商組合性之問題，當某些工作被指派至一網格式的分散式系統時，彼此間具有關聯性的工作必需與其它不同的分散系統作資訊交換的動作。本研究分別提出連續型粒子群優化演算法及二元型粒子群優化演算法以解決網格排程問題及探討相關參數對解之影響。
本研究之目的在於希望能最小化網格環境中之網格運算之最大成本，其成本包含運算成本與通訊成本，模擬之結果顯示本研究所提出的演算法確實能解決網格排程問題。

The grid scheduling problem is concerned with some tasks assigning to a grid distributed system that the relative tasks have to exchange information on different grids. This theses presents a particle swarm optimization（PSO）and a discrete particle swarm optimization (DPSO) to solve the grid scheduling problems. The objective is to minimize the maximum cost of the Grid, which includes computing cost and communicate cost. Simulation results show that the grid scheduling problem can be solved efficiently by the proposed method. Meanwhile some factors which are not important in PSO, are also demonstrated in this work.

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