In any modern industry, automation takes a vital role in manufacturing an end product. However even today, we could see in many industries including automobile industry, the sub-assemblies and assemblies that involve manual assembling aided by some level of automation. In these cases, the total processing time or assembling time has to be optimized to complete the product at the earliest. Many categories of problems are framed and solved using many techniques. One such type, the permutation flow shop scheduling problems deal with the sequencing of jobs in the available machines/ work stations. This paper analyses the popular NEH heuristic algorithm in this area and a few more simple heuristic algorithms using Taillard benchmark problem instances. The parameter to be optimized being the makespan (total completion time). First two jobs are selected as the initial partial makespan after initially ordering the jobs according to their total processing times. The powerful job insertion technique is used to insert other jobs to obtain the final sequence. Two more initial ordering of jobs and initial partial sequences are also considered and the makespans are computed. The results are analyzed using ANOVA. Â© 2017 Elsevier Ltd.
|Journal||Data powered by TypesetMaterials Today: Proceedings|
|Publisher||Data powered by TypesetElsevier BV|