No abstract

Scheduling is considered to be a major task to improve shop-floor productivity. The job shop problem is under this category and is combinatorial in nature. Research on optimization of job shop problem is one of the most significant and promising areas of optimization. This paper presents an application of the global optimization technique called tabu search to the job shop scheduling problem. An easily implementable algorithm for the problem of finding a minimum makespan in a job shop is presented. The method employs critical paths and blocks of operations. The algorithm is based on a specific neighborhood and dynamic tabu length strategies. A neighboring solution is a solution obtained by permuting two successive and critical operations that use the same machine. Tabus are useful to help the search move away from previously visited portions of the search space and thus perform more extensive exploration. Experiments using well-known bench mark problems are carried out to check the performance of the proposed method.

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.