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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
