Open AccessProject Scheduling using Event Based Scheduler with ABC
Author(s) -
Sarojini Yarramsetti
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a5026.119119
Subject(s) - computer science , scheduling (production processes) , dynamic priority scheduling , schedule , ant colony optimization algorithms , probabilistic logic , cluster analysis , two level scheduling , fair share scheduling , operations research , mathematical optimization , artificial intelligence , engineering , operating system , mathematics
Scheduling is the first and foremost step for every project implementation. Project scheduling could be a mechanism to communicate what tasks has to be compelled to get done and which resources are going to be allotted to finish those tasks in what timeframe. Project scheduling occurs during the planning phase of the project. The problem comprises the correct assignment of employees to the various tasks that frame a software project, casing in time and cost limitations. To accomplish this objective, this paper presents and discusses the EBS with ACO, FCM clustering and EBS with ABC and the conclusions are drawn from it. First, to schedule human resources to tasks we implement Event based scheduler with the Ant colony optimization algorithm (ACO) for probabilistic optimization, second, for fast scheduling we implemented Fuzzy c means clustering to assign similar data points of employees to clusters so that the searching space will be reduced. Third, for optimum scheduling we apply Artificial Bee Colony algorithm with Event Based Scheduler. Artificial bee colony (ABC) is an optimization algorithm based on stochastic calculation which has demonstrated good search capacities on numerous advancement issues. Based on these findings we briefly describe the scheduling with FCM-EBS with ABC prompt optimum values