Open AccessA Crew Model using GAIIPDM in Repetitive Projects
Author(s) -
Jeeno Mathew*,
Brijesh Paul
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c6179.098319
Subject(s) - crew , schedule , task (project management) , computer science , plan (archaeology) , genetic algorithm , operations research , simple (philosophy) , project plan , quality (philosophy) , project management , industrial engineering , machine learning , systems engineering , engineering , aeronautics , procurement , philosophy , archaeology , epistemology , marketing , business , history , operating system
Several indistinguishable or comparative tasks/works in a project are generally alluded to as repetitive projects. A project have group of tasks which is repetitive in nature in all over the project or a similar plan in different positions are commonly known as repetitive project. In repetitive project businesses, distinctive crew choices are accessible for each task, and selecting the best choice to a task is a noteworthy test for administrators of a project. Since acquiring optimum results is found computationally escalated for this type of problems, a modified Genetic Algorithm based technique is developed to schedule projects to satisfy different goals like minimizing total task time and the total expenditure of the project, with the constraints of precedence connections between different tasks, precedence connections between different sites and the due time within which different tasks to be finished. The performance of the proposed method is compared with solutions created using existing algorithms like simple GA and ABC. Exact solutions generated by solving the developed mathematical model is utilized for validating the solutions acquired by modified GA. The computational outcomes demonstrate that the proposed GAIIPDM methodology performs significantly well in terms of quality of solutions.