No idle flow shop scheduling models for optimization of machine rental costs with processing and separated setup times - Singla, Shakuntla; Kaur, Harshleen; Gupta, Deepak; Modibbo, Umar Muhammad; Kaur, Jatinder (Frontiers in Applied Mathematics and Statistics, 2024)
Scheduling is one of the many skills required for advancement in today’s modern industry. Flow-shop scheduling is a typical optimization problem. Scheduling issues for flow shops are NP-hard and challenging. In the current work, a two-stage flow shop scheduling model without idle constraint is studied, where processing time and machine setup time are taken into distinct considerations. A correlation exists between probabilities, the processing time of jobs, and the setup time. The study aims to create a heuristic algorithm that, when put into operation, optimally processes jobs and guarantees in the shortest possible makespan. This will eliminate machine idle time and reduce machine rental costs. The effectiveness of the suggested technique is demonstrated by several computational examples produced in MATLAB 2021a. The results are compared with the existing approaches that Johnson, Palmer, NEH, and Nailwal have shown.