A study on multi-resources scheduling optimization using tabu search method.

• Main Authors: Po-Wen Hsaio, 蕭博文
• Other Authors: Nai-Hsin Pan
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/89419072347062614976

碩士 === 朝陽科技大學 === 營建工程系碩士班 === 90 === Abstract There are three objectives on the construction project resource scheduling: (1) to let all of the activities get their resources and then complete the works before the required finish date; (2) to make resource allocation and utilization efficiently to reduce the delay possibility of the works when the capacity; (3) to utilize there sources more effectively to get the better financial management performance and also increase our revenue. Considering the conditions of the constrained resources, resources scheduling become more difficult as of the scope of construction engineering projects become larger and more complex. Although using traditional models to solve this sort of problems could obtain the optimal solution, the process of evaluation will be complex and inefficiency. In the previous studies, most of the studies focus on finding a new algorithm such as genetic algorithm to improve the speed of searching feasible solutions. The research uses a new algorithm, namely Tabu search, to solve the problem of resource scheduling which are constrained. Tabu search method was widely applied to solve the various kinds of combinatorial optimization problems in the industrial engineering area and got distinguished results. It is based on introducing flexible memory structures in conjunction with strategic restrictions and aspiration levels as a means for exploiting search spaces. The research will explore the feasibility of this algorithm and implements the concept of tabu search method to set up a new model considering constrained resources. The research found using this new model built by tabu search could solve the multi-resources problems of construction project, but also provide a precise solutions in some cases, Furthermore, this model also makes improvement on the disadvantages of traditional models and both make the better solution quality and higher efficiency of evaluation.