A Multiobjective Seagull Optimization Algorithm For Solving Flow Shop Scheduling Problem – A Case Study

Abstract

In the manufacturing industries, the most complicated scheduling crisis is the flowshop scheduling problem (FSP) and is proven to be an NP-hard problem in real-world cases. In FSP, the chief issue in this problem is handing over jobs in every stage to machines and choosing the jobs processing order allotted to each machine. This crisis comprises three sub-decisions: assigning jobs to factories, picking suitable machines for jobs, and establishing the processing order on each machine.  In this paper, a FSP has been investigated by considering objective functions like makespan, mean flow time and machine idle time. By reducing the make span, mean flow time and the machine idle time the energy consumption of the company could be reduced. To show the outcome of the proposed methodology, it is implemented in MATLAB by taking real-world scenarios. With the benefit of the seagull optimization procedure, the manufacturing field has the power to determine the processing order on each machine by appropriately selecting jobs on specific machines. The mathematical model assists the proposed model in achieving an efficient outcome meanwhile maintaining the energy constraint model.