PYTHON-BASED TOTAL ELAPSED TIME OPTIMIZATION IN FLOW SHOP SCHEDULING

Python-based total elapsed time optimization in Flow Shop Scheduling is a computational approach for solving a flow shop scheduling problem to minimize total elapsed time. This book covers the basics of Operations Research, scheduling, Flow Shop Scheduling Models (FSSM), and the use of Python in Optimization techniques. It also elaborates on the method of minimizing the elapsed time for two-stage flow shop scheduling in a Python approach with suitable algorithms and numerical examples. The last chapter is an extension of the study to a two-stage FSSM, where processing times are associated with probabilities, and tackles uncertainty in practical industrial applications. Using computational approaches described in Python, the book offers fast methods to determine optimal sequences of jobs more accurately, with less computational load, and intelligently for use in scheduling problems.