考虑新技能学习机制的软件项目调度人工蜂群算法

Artificial bee colony algorithm for software project scheduling considering new skills learning mechanism

考虑新技能的学习机制,建立软件项目调度问题的数学模型.该模型融入员工对新技能的学习、新技能熟练度的增长、投入度的自适应变化以及已有技能熟练度变化等实际因素,通过寻找最佳员工任务分配方案,最小化软件项目的工期和成本.为求解该模型,提出一种引入问题启发信息的离散人工蜂群算法.将多元学习策略应用于引领蜂阶段,在保证种群多样性的同时,加强算法全局搜索能力.在跟随蜂阶段采用一种基于启发信息的变异机制,保留最优个体中契合度较高的员工信息,并根据不同个体目标值的优劣采用相异的变异方式,针对性地进行搜索,以增强算法的局部寻优能力.实验结果表明,与已有算法相比,所提算法在不同规模的软件项目调度问题中均能够搜索到更优的分配方案.

Considering the learning mechanism of new skills, a mathematical model of the software project scheduling problem is established. The model integrates some practical factors such as learning of new skills, increase of the new and existing skill proficiencies, and adaptive changes of dedications. Both duration and cost of the software project are minimized by finding the best assignment of employees to tasks. To solve the model, a discrete artificial bee colony algorithm incorporating heuristic information is proposed. A multi-learning strategy is applied to the employed bees phase to enhance the global search ability of the algorithm while maintaining the population diversity. In the onlooker bees phase, a mutation mechanism based on heuristic information is adopted, where information of the employees with higher fit in the optimal individual is retained, and distinct mutation operators are employed on different individuals based on their objective values to improve the local search ability. Experimental results show that compared with the existing methods, the proposed algorithm can find a better allocation in software project scheduling problems with increasing scales.