A GA-based Approach for Solving Project Selection and Scheduling Problems in a Multiple-Department Environment

碩士 === 國立中央大學 === 工業管理研究所 === 93 === Abstract: Before implementing projects, project selection is a very important proceeding work. An organization can’t possibly implement all coming projects because of some limitations such as budgets and human resources. Every project selection result sifting f...

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Bibliographic Details
Main Authors: Pei-Sheng Chen, 陳貝生
Other Authors: Ying-Chin Ho
Format: Others
Language:en_US
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/04695063227818818793
Description
Summary:碩士 === 國立中央大學 === 工業管理研究所 === 93 === Abstract: Before implementing projects, project selection is a very important proceeding work. An organization can’t possibly implement all coming projects because of some limitations such as budgets and human resources. Every project selection result sifting from candidate projects in an organization can be called a “project portfolio”. Further, after getting a project portfolio in an organization, deciding when to implement (schedule) these selected projects is also an important issue. By scheduling, we can make the resource consumption in each period satisfies the budget constraints. In reality, organizations in a firm such as departments are facing this problem. Multiple departments have multiple candidate projects to choose in a company. How to decide the project portfolio in each department so as to gain the overall maximum profit in a firm? This is a very complex problem in reality. Although project selection and scheduling problem has been discussed in depth and several related models have been proposed, none of them discussed this problem in a multiple-department environment. For this reason, our paper focuses on the project selection and scheduling problem in a multiple-department environment. Owing to project selection and scheduling problem belongs to a typical combination problem, we try to propose a problem-specific genetic algorithm in project selection and scheduling problem to find a satisfactory result in our paper. In addition, due to deciding the parameters of the proposed genetic algorithm are necessary, Taguchi method will be applied in the process for deciding the most suitable parameters.