Project Scheduling using Event Based Scheduler with ABC
Sarojini Yarramsetti

Sarojini Yarramsetti is a Assistant Professor in the Department of Computer Science Engineering, Hindusthan College of Engineering and Technology, Coimbatore, India.
Manuscript received on October 12, 2019. | Revised Manuscript received on 24 October, 2019. | Manuscript published on November 10, 2019. | PP: 3947-3955 | Volume-9 Issue-1, November 2019. | Retrieval Number: A5026119119/2019©BEIESP | DOI: 10.35940/ijitee.A5026.119119
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Abstract: 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.
Keywords: Artificial Bee Colony (ABC), Event Based Scheduler (EBS), Fuzzy C Means (FCM), Resource Constrain Project Scheduling (RCPS), Task scheduling
Scope of the Article: Fuzzy Logics