Paper Info
Title
A parameter-tuned genetic algorithm for the resource investment problem with discounted cash flows and generalized precedence relations
Abstract
A resource investment problem with discounted cash flows (RIPDCF) is a project-scheduling problem in which (a) the availability levels of the resources are considered decision variables and (b) the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, the RIPDCF in which the activities are subject to generalized precedence relations is first modeled. Then, a genetic algorithm (GA) is proposed to solve this model. In addition, design of experiments and response surface methodology are employed to both tune the GA parameters and to evaluate the performance of the proposed method in 240 test problems. The results of the performance analysis show that the efficiency of the proposed GA method is relatively well.
Year
DOI
Venue
2009
10.1016/j.cor.2009.01.016
Computers & OR
Keywords
DocType
Volume
project cash,GA parameter,resource investment problem,proposed GA method,project-scheduling problem,availability level,generalized precedence relation,performance analysis show,parameter-tuned genetic algorithm,test problem,discounted cash flow,proposed method
Journal
36
Issue
ISSN
Citations 
11
Computers and Operations Research
17
PageRank 
References 
Authors
0.91
8
3
Name
Order
Citations
PageRank
Amir Abbas Najafi115313.32
Seyed Taghi Akhavan Niaki262457.47
Moslem Shahsavar3261.46