Flexible Job Shop Scheduling Problem with Parallel Batch Machines to Minimize Total Weighted Flowtime with Machine Eligibility Restrictions in Automobile Gear Manufacturing Industry
R. Murugesan a, M. Rajeshwari b, Praveena Kumara K.M c and G. K. Jagatheswari d
aDepartment of Mathematics, REVA University, Bangalore, India. Email id: contactmurugu@gmail.com.
bDepartment of Mathematics, School of Engineering, Presidency University, Bangalore, India. praveenmsk82@gmail.com
c*Department of Mathematics, REVA University, Bangalore, India. rajeakila@gmail.com.
dDepartment of Science and Humanities, PES University-EC Campus, Bangalore-560 100, India. jagatheswarigk@pes.edu
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Abstract:
In this article, we address a Flexible Shop Job Scheduling Problem with parallel machine batch processing for minimizing total weighted flowtime of the production of automotive gears manufacturing industry. Scheduling has specifically addressed the bottleneck functioning of the Pre-Heat treatment stage of the vehicle gear manufacturing process. Numerous real-world scenarios have been taken into account, including machine eligibility constraints, sequence-dependent setup delays, and unequal release times. Dynamic beginning conditions are taken into consideration using a mathematical model that has been suggested. It is determined that the scheduling problem is NP-hard and used the meta- heuristic algorithm that is a Modified Clonal Selection Algorithm by Positive Selection method (PSMCSA) have been offered as ways to approach the issue. The performance of the suggested algorithms is assessed based on planned computational experiments. The proposed heuristic algorithms may consistently produce solutions that are close to the optimal ones as calculated by statistics in an acceptable amount of time, according to extensive computational assessments.
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