Modified Neh Heuristic On Makespan Reduction In Permutation Flow Shop Problems - Chong, Zheng Ziao (2015)
Permutation flow shop problem (PFSP) is one of the commonly reviewed machine environments in scheduling problems. The order sequence for each process remains unchanged for all machines. Few algorithms have been developed to decide the sequence of n jobs and m machines that can minimize makespan in flow shops. Throughout the past 30 years, the NEH heuristics developed by Nawaz, Enscore and Ham has been commonly regarded as the best heuristic for minimizing the makespan in permutation flow shops. Due to these findings, NEH heuristics is selected as the basis of this study. Modification is done to enhance the objectives of this study, which is makespan and idle time reduction. In this study, a total of 109 flow-shop problems were solved with the number of machines and jobs being set at a range of 4 to 25. 100 problems were carried out using numerical assessments. The process times of the jobs were randomly generated within the range of 1 to 10 using Excel spreadsheets. Whereas the remaining 9 sets of tests were carried out using real world case studies. In each case study, the company involved was provided with a surface mounting technology (SMT) service. It has the capability of planning schedules by adopting the backward scheduling technique. The proposed heuristic, NEH-M will be compared to both the historical production schedule and NEH schedule in order to verify and validate the performance of the proposed idea. The performance of the NEH-M heuristics was computed using the error deviation (ED) formula. The generated results gained through Excel modeling show that the NEH-M heuristics outperforms the historical production schedule in all conditions. On the other hand, when the NEH-M heuristics is compared to the NEH heuristics, the overall performance of makespan reduction is underperforming while the overall performance of idle time reduction is over performing when there are large numbers of machines and jobs.