Multi-Attribute Real Time Resource Approximation Based Efficient Job Shop Scheduling

The problem of job shop scheduling has been approached in several methods and still the performance on job shop scheduling. To overcome the deficiency in job shop scheduling, the author present an ant based multi attribute real time resource approximation technique. Initially the method generates number of ants according to number of resources available. The multi attribute real time resource approximation technique considers make span time, waiting time, resource utilization as the name suggest. The method first generates the possible sequences in multi level for each job. The sequence is generated in combinatory where each job will be placed in first in different sequence. In the second stage, for each sequence the method estimates the sequence weight according to make span time, waiting time and resource utilization value. Finally, based on computed sequence weight, the method selects a single sequence to schedule the job set. The method produces higher scheduling performance and reduces the time complexity as well.