Software Project Scheduling Using Ant Colony and Artificial Bee Colony Algorithm

Journal Title: Gazi Mühendislik Bilimleri Dergisi - Year 2018, Vol 4, Issue 2

Abstract

The success rate of software projects is still not at the desired level despite of the technological advances. The vast majority of software projects can not be delivered at the desired specifications or can be delivered beyond the planned budget and time. The software project schedule is one of the important factors that influence this success. Due to it includes parameters such as human resource, time, cost, and process sequence of activities, state space is too big for software project scheduling. So it is difficult to create a software project schedule for software project managers. In this study, using human resource and activities these resource can do, it is tried to obtain minimum project completion time while creating software project schedule using ant colony and artificial bee colony optimization algorithm and results are analyzed. According the results obtained, both methods are successful in software project scheduling. Although the processing time of the artificial bee colony algorithm is slower than ant colony optimization algorithm, it has been determined that when the number of colony / food source is increased, it is converged to minimum project completion time faster than the ant colony algorithm.

Authors and Affiliations

Keywords

Related Articles

Optimal Energy Mix Determination to Regulate Uncertain Production of HPP and SPP: Malatya City Case Study

One of the major disadvantages of renewable energy sources is that they have a variable and unstable characteristic. Uncertainly changing energy production over time makes it difficult to maintain supply-demand power bal...

LIFE Füzyon Reaktöründe Yüksek Sicaklikta Elektroliz Yöntemi İle Hidrojen Üretimi

Bu çalışmada, lazer sürücülü füzyon reaktörünün (LIFE) zamana bağlı nötronik performansı ve bu performansa bağlı olarak  hidrojen üretim potansiyeli yüksek sıcaklıkta elektroliz (HTE) yöntemi kullanılarak incelenmiş...

Production of NiO/ZnO Nanocomposite Particles by Sol-Gel Technique

In recent years, the need for new generation and critical materials has brought the nanoscale materials to the center of modern research. In this study, the production of NiO/ZnO nanocomposite particles by sol-gel method...

LabVIEW based Continuous Monitoring of Separately Excited DC Motor

In this day and age the applications of electrical machines are diverse and overall quite advantageous to our current way of life. For this purpose, we have to make sure that the machines themselves are operating properl...

Modeling of Mating / Seperating Force in Snap-Fit Joints by Artificial Neural Networks Method by Material Type and Friction Coefficient

In this study, an Artificial Neural Network Model has been developed to calculate the mating / separating forces of Snap-Fit joints. In order to determine the mating / separating force of this calculation using Computer...

Download PDF file
  • EP ID EP530075
  • DOI -
  • Views 77
  • Downloads 0

How To Cite

(2018). Software Project Scheduling Using Ant Colony and Artificial Bee Colony Algorithm. Gazi Mühendislik Bilimleri Dergisi, 4(2), -. https://europub.co.uk/articles/-A-530075