An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
A project management quality cost information system for the construction industry
Information and Management
Information systems project management: an agency theory interpretation
Journal of Systems and Software
Understanding software project risk: a cluster analysis
Information and Management
Building knowledge discovery-driven models for decision support in project management
Decision Support Systems
IEEE Transactions on Knowledge and Data Engineering
An empirical analysis of risk components and performance on software projects
Journal of Systems and Software
Using fuzzy decision making for the evaluation of the project management internal efficiency
Decision Support Systems
Expert Systems with Applications: An International Journal
Two stages of case-based reasoning - Integrating genetic algorithm with data mining mechanism
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A recommender mechanism based on case-based reasoning
Expert Systems with Applications: An International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Project management is an experience-driven and knowledge-centralized activity. Therefore, project managers require some assistance to reduce the uncertainty at the early stage of constructing project plans. To overcome the predicament faced by project managers, this investigation proposes a hierarchical criteria architecture (HCA) to enable project managers to describe project requirements adequately. Furthermore, to solve HCA problems, a revised case-based reasoning (RCBR) algorithm, is presented and a recommender system for software project planning is implemented, based on multiple objectives decision techniques and the mining approach. Finally, the proposed RCBR algorithm is successfully applied to analyze 41 real projects from a software consultancy in Taiwan. Experimental results demonstrate that RCBR can efficiently provide related information to help project managers to construct project plans at an early stage. Additionally, the knowledge discovery process of RCBR provides project managers with results similar to what-if analysis. The knowledge can enable project managers to obtain feasible information to re-schedule project resources, and bargain with their customers in the early project planning stage.