IT外包进度风险控制的自适应禁忌搜索算法

针对委托代理模式下的IT外包项目的进度风险控制问题构建了双层结构的优化模型.设计了自适应禁忌搜索算法对模型进行求解，该算法将多样化搜索机制与禁忌搜索相结合，在算法运行过程中，根据适应值的反馈自动调整禁忌搜索强度与多样化搜索力度；同时，应用贪婪策略构造初始解，循环交替应用两种邻域结构提高算法寻优能力.实验结果表明，进度风险控制显著地降低了IT外包项目的拖期风险，同时使委托方和代理商双方实现收益最大化.将自适应禁忌搜索算法的实验结果分别与遗传算法、模拟退火算法、禁忌搜索算法、自适应遗传算法和自适应模拟退火算法的实验结果进行了比较：在收敛程度和稳定性方面自适应禁忌搜索算法优于其它算法，并且随着问题规模的增加，该算法的优势更为明显.

Adaptive Tabu Search Algorithm for IT Outsourcing Schedule Risk Control

We construct an optimization model with two-tier structure to quantify the schedule risk control of IT outsourcing projects based on the principal-agent model. We design an adaptive tabu search algorithm to solve the model. The improved algorithm combines diversified search mechanism with loop execution of tabu search. The intensity of tabu search and the strength of diversified search are automatically adjusted according to the feedback of fitness value. While, the improved algorithm applies the greedy strategy to construct the initial solution. Two neighborhood structures are used crosswise to improve algorithm optimization ability. The experimental results show that schedule risk control significantly reduces the risk of delays in IT outsourcing projects, and maximizesthe benefits of both the principal and the agent. Compared with the genetic algorithm, simulated annealing algorithm, basic tabu search algorithm, adaptivegenetic algorithm and adaptive simulated annealing, the improved algorithm is obviously superior to other algorithms in terms of convergence degree and stability. As the scale of the problem increases, the superiority of algorithm is more obvious.