The Need of Genetic Algorithms (GAs) in Project Scheduling

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2019 by IJETT Journal
Volume-67 Issue-11
Year of Publication : 2019
Authors : Nile Tushar Rambhau, Kanneti Lakshmi Tanuja, Murlidhar Revu Rathod, Mohammed Yaser Noaman
DOI :  10.14445/22315381/IJETT-V67I11P223


MLA Style: Nile Tushar Rambhau, Kanneti Lakshmi Tanuja, Murlidhar Revu Rathod, Mohammed Yaser Noaman  "The Need of Genetic Algorithms (GAs) in Project Scheduling" International Journal of Engineering Trends and Technology 67.11 (2019):144-147.

APA Style:Nile Tushar Rambhau, Kanneti Lakshmi Tanuja, Murlidhar Revu Rathod, Mohammed Yaser Noaman. The Need of Genetic Algorithms (GAs) in Project Scheduling  International Journal of Engineering Trends and Technology, 67(11),144-147.

The first and foremost objective of this paper is to provide an effective solution for software project scheduling i.e. through implementation of Genetic Algorithms in project scheduling techniques. The main theme of software project scheduling is to break a complete project into several subtasks, which in whole will be a complete project. The software project manager has to keep track the schedule and has to stick on that schedule to the maximum. The schedule has to be strictly followed which can be achieved by periodic project status meeting with the members involved in the project. This is achieved with the help of Genetic Algorithm. The Existing techniques are increasingly considered to be inadequate for modeling the unique characteristics of today’s software projects. The main reason is that, differently from other projects, a software project is a people-intensive activity and its related resources are mainly human resources. The tools based on the traditional project management techniques usually regard task scheduling and human resource allocation as two separated activities and leave the job of human resource allocation to be done by project managers manually resulting in inefficient resource allocation and poor management performance. Hence, authors are recommended to implement Genetic Algorithm in project scheduling for effective results.


[1] Wei-Neng Chen and Jun Zhang ?Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler IEEE Transactions on Software Engineering, vol. 39, no. 1, January 2013.
[2] J.Dugan H. Byrne, and G.J. Lyons, “A Task Allocation Optimizer for Software Construction “, IEEE Software, vol.21, no.3, pp.76-89, May, June 2004.
[3] A barreto, O. Barros, CM.L. Werner, “Staffing a software project: A Constraint Satisfaction and Optimizationbased approach “, Computers& Operations Research, vol.35, pp. 3073-3089, 2008.
[4] C.K. Chang and M. Christensen, ?A Net Practice for Software Project Management, IEEE Software, vol. 16, no. 6, pp. 80-88,Nov./Dec. 1999.
[5] CARL K. CHANG – Genetic Algorithms for Project Management, Department of EECS (M/C 154), The University of Illinois at Chicago, Chicago, IL 60607, USA.
[6] Raymond Chiong ,”A Comparison between Genetic Algorithms and Evolutionary Programming based on Cutting Stock Problem” , Engineering letters,14:1,EL_14_1_14(Advance online publication: 12 February 2007).
[7] Genetic Algorithms: Colin Reeves, School of Mathematical and Information Sciences, Coventry University.
[8] Chongmin Li- “Priority Base fair Scheduling: A Memory Scheduler Design for Chip –Multiprocessor Systems”
[9] R Hinterding and L Khan, “Genetic algorithms for cutting stock problems: with and without contiguity,” in progress in evolutionary computation (X Yao, ed.), vol. 956 of lecture notes in Artificial Intelligence, Berlin pp. 166-186 springer, 1995.
[10] D. Fogel, “A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems,” Simulation vol. 64, no.6, pp. 397-404, 1995.
[11] R Hinterding, “Mapping, order-independent genes and the knapsack problem,” in proceedings of the first IEEE conference on evolutionary computation (ICE ?94), Orlando, Florida, USA, 1994, pp. 13-17.
[12] E.A. Falkenauer and A. Delchambre, “ A genetic algorithm for bin packing and line balancing , “in proceedings of the IEEE International conference on robotics and automation(RA92),Nice, France,1992 pp. 1186-1193.
[13] L. Davis, ed., Handbook of Genetic Algorithms, New York Van Nostrand Reimhold, 1991.
[14] Battu HanumanthaRao “A Brief View of Project Scheduling Techniques” IJERT Vol.2-Issue 12 December -2013.
[15] B. Boehm et al., Software cost Estimation with COCOMO II. Prentice-Hall, 2000.
[16] B. Bohem “Software Engineering Economics, Prentice Hall, 1981.
[17] C.K. Chang, M.J. Christensen, C. Chao, and T.T. Nguyen, ?Software Project Management Net: A New Methodology on Software Management, ?Proc. 22nd Ann.Int?l Computer Software and Applications Conf., 1998.
[18] C. Blum, ?Beam-ACO-Hybridizing Ant Colony Optimization with Beam Search: An Application to Open Shop Scheduling, Computers and Operations Research,vol. 32, pp. 1565-1591, 2005.

Genetic Algorithms (GAs), Project Scheduling, Evolutionary Computing (EC), Genetic Programming