en Optimization Techniques Optimization Techniques پژوهشي Research <span style="font-size:11pt"><span style="line-height:normal"><span style="text-autospace:none"><span style="font-family:Calibri,sans-serif"><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">This paper presents a model for minimizing the makespan in the flow shop scheduling problem. Due to the impact of increased workloads, flow shops are becoming more popular and widely used in industries. To solve the challenge of minimizing makespan, a </span></span></span></i><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times="">Hybrid-Heuristic-Metaheuristic-Genetic-Algorithm</span></span></i><i> </i><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">(HHMGA) is proposed. The proposed HHMGA algorithm is tested using the simulation software and demonstrated with steel industry data. The results are compared with those of the best available flow shop problem algorithms such as Palmer&rsquo;s slope index, Campbell-Dudek-Smith (CDS), Nawaz-Enscore-Ham (NEH), </span></span></span></i><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">genetic algorithm (GA) and particle swarm optimization (PSO)</span></span></span></i><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">. According to empirical results and relative differences from the lower bound, the proposed technique outperforms the three heuristics and two metaheuristics algorithms in three of six cases, while the remaining three produce the same results as the NEH </span></span></span></i><i><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">heuristic. In comparison to the steel industry&#39;s regular job scheduling technique, the simulation model based on HHMGA can save 4642 hours. It was discovered that the suggested model enhanced the job sequence based on the makespan requirements.</span></span></span></i></span></span></span></span> ,Makespan,Scheduling,Heuristic,Metaheuristic,Genetic algorithm,Lower bound 1 16 http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-2635-1&slc_lang=en&sid=1 PRASAD BARI prasad.bari@fcrit.ac.in 1800319475328460011729 1800319475328460011729 Yes Fr. C. Rodrigues Institute of Technology PRASAD KARANDE pmkarande@me.vjti.ac.in 1800319475328460011730 1800319475328460011730 No Veermata Jijabai Technological Institute