In the background of service resources optimizing management in cloud computing, this paper conducts a research on the time-window based Non-identical Parallel Machine Schedule Problem.To get the most tasks done,minimizing delay time is chosen to be the objective of the mathematical model and an ant colony algorithm is given.This paper deploys different parameters,and having designed every parameter of the algorithm,this paper carries out a discussion of how to import the fairness of resource allocation into the algorithm, and compares different scheduling results under the condition of whether to consider fairness elements or not with simulation examples..The result indicates that the modified ant colony algorithm could be well applied in the parallel scheduling in cloud computing.It can find the optimal solution satisfied the constraint condition with a fast convergence rate.

文章通过分析库存控制过程中碳排放的要素,构建出基于碳排放成本的库存控制模型,对低碳供应链中的库存控制的要素进行了分析,并给出了具体的实现方案。该模型有利于进一步提升供应链的核心竞争力,推动低碳供应链管理的深入研究。

Under the context of deicing in the airport and in order to solve a kind of non-identical parallel multi-machine schedule problem for minimizing the number of passengers delayed,an ant colony algorithm is suggested.Considering the characteristic of scheduling model and its'constraints,an improved pheromone update strategy is developed.The result is superior to that of traditional FIFO algorithm,indicates that the improved ant colony algorithm is valid and can fit for non-identical parallel multi-machine schedule problem.

Under the context of airplane deicing, this paper aims to do a research on the unrelated parallel scheduling of service resources with flexible time window. To deal with more tasks, minimizing delay time is chosen to be the objective of the mathematical model and a modified ant colony algorithm is given. With full consideration of the practical problem and constraints, update policy of pheromone and settings of heuristic factors are suggested. The feasibility and rationality are proved by a simulation example. The modified ant colony algorithm outperforms FIFO method and could be well applied in the unrelated parallel scheduling issues with flexible time window.

Under the context of deicing in the airport, and in order to solve a kind of Non-identical Parallel Multi-machine Schedule Problem for minimizing the number of passengers delayed, an ant colony algorithm was proposed. Considering the characteristic of scheduling model and its constraints, an improved pheromone update strategy was developed by deploying different parameters. Simulation was made for proving the effectiveness of the algorithm, and the sensitivity analysis was conducted. Besides, the improved ant colony algorithm was compared further with FIFO algorithm used in realistic backgrounds. In all, the result indicated that the improving ant colony algorithm was valid, and it can fit for large-scale non-identical parallel Multi-machine scheduling problem.