| Summary: | 碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 95 === Optimal expansion problem of competence set is a novel and a valuable method for decision makers. It expanses the acquired competence sets effectively under the constraints of solving the problem until all of the competence sets needed (the true competence set) are achieved. However, there are some drawbacks existed in the way of traditional competence sets expansion:
(1) It’s only suitable for the problems of acyclic path and only dealing with the cost symmetrical function.
(2) It only considers about the expansion of individual competence sets limited to its own resources and skills.
(3) It never discusses the case of multilevel competence set problems.
(4) It ignores the issue of alternative optimal solution.
According to the above problems, the research uses the concept of background competences to construct an optimal competence set expansion model, of which the mathematical programming method and deduction graph are used.
To overcome the problems, there are following contributions:
(1) Build an「Optimal Competence Set Expansion」modeling: it can deal with the cyclic path problem and cost asymmetric function.
(2) Build an「Incorporating Competence Set Expansion」modeling: it merges cooperation game and competence set expansion concept in order to find out the optimal strategy combination through the change of resources or the share of skills and create the maximum benefit for all participators.
(3) Build an「Multilevel Competence Set Expansion」modeling: it introduces fuzzy logic theory to obtain competences in certain order. Based on the level difference, this model can achieve the goal with the minimum cost and the overall proficiency of the maximum skills
(4) Use「Alternative Optimal Solution」method: it can find out all the optimal solutions. In practice, alternative optimal are useful and essential because they allow the decision makers to choose from many solutions without experiencing any deterioration in the objective function, and the decision makers can select the final optimal solution based on his preferences.
|
|---|
