.png){kind=icon}
.png){kind=icon}
Return
Firework-based software project scheduling method considering the learning and forgetting effect
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-018-3165-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The learning and forgetting ability, as the inherent characteristics of the employees, have a great impact on the software development process. By using the idea of WLC learning and VRVF forgetting models, an novel learning and forgetting model is constructed for software project scheduling problem to measure the dynamic skill levels. Taking the cost and duration as the optimization objectives, corresponding software project scheduling model considering the learning and forgetting effect is formed. The improved multi-objective firework algorithm with a novel encoding scheme is present. The crossover-explosion operator is introduced to enhance the information exchange between the better sparks or fireworks. A novel reservation strategy with two archives is proposed to avoid the ineffective search around the local optimum. Experimental results indicate that the learning ability plays a positive role on the optimal scheduling schemes and the forgetting effect is the opposite. The duration and cost of the project are inversely proportional to the learning coefficient and directly proportional to forgetting coefficient. By comparing the scheduling schemes from NSGA-II and original FA, the proposed method shows the better scheduling performances.
Keywords:
Firework algorithm
Learning effect
Forgetting effect
Software project scheduling
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.5
Papers:
1.0W
Citations:
2.1W
Organization
No organization information available