Multi-objective project management decisions in fuzzy environments

• Main Authors: Lin Hsueh-Mao, 林學茂
• Other Authors: Liang Tien-Fu
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/03694624555024727254

碩士 === 修平技術學院 === 精實生產管理研究所 === 99 === Project management (PM) issues have long attracted interest from both practitioners and academics. In practical PM decision problems, environmental coefficients and related parameters are frequently imprecise/fuzzy in nature, and a decision maker (DM) must simultaneously consider various conflicting objectives in a framework of imprecise aspiration levels. This work develops an interactive two-phase possibilistic linear programming (PLP) approach for solving the PM decision problems with multiple goals in a fuzzy environment. The original fuzzy multi-objective linear programming (MOLP) model designed here attempts to simultaneously minimize total project costs and total completion time with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available budget. The auxiliary fuzzy MOLP problem resulting from the treatment of the imprecise objective function can be converted into an equivalent ordinary single-goal linear programming form using the linear membership functions to specify the fuzzy objectives of the DM, together with the minimum and weighed averaging operators to aggregate fuzzy sets. Moreover, a systematic solution procedure is developed to provide a suitable fuzzy decision-making process of the DM to solve PM decision problems, enabling a DM to interactively modify the fuzzy data and parameters until a preferred satisfactory efficient solution is derived. Additionally, a real-world industrial case is utilized to demonstrate the feasibility of applying the proposed two-phase PLP approach to MRP decision problems and several significant management implications and features regarding the practical application of the proposed approach are presented. Overall, the main contribution of this work lies in presenting the fuzzy mathematical programming methodology for solving the PM decision problems with constrained resources in uncertain environments. Computational methodology developed in this work can easily be extended to any other situations and can effectively handle the realistic PM decisions.