Flow-Shop Scheduling with Transportation Capacity and Time Consideration

Planning and scheduling is one of the most important activity in supply chain operation management. Over the years, there have been multiple researches regarding planning and scheduling which are applied to improve a variety of supply chains. This includes two commonly used methods which are mathematical programming models and heuristics algorithms. Flowshop manufacturing systems are seen normally in industrial environments but few have considered certain constraints such as transportation capacity and transportation time within their supply chain. A two-stage flowshop of a single processing machine and a batch processing machine are considered with their capacity and transportation time between two machines. The objectives of this research are to build a suitable mathematical model capable of minimizing the maximum completion time, to propose a heuristic optimization algorithm to solve the problem, and to develop an applicable program of the heuristics algorithm. A Mixed Integer Programming (MIP) model and a heuristics optimization algorithm was developed and tested using a randomly generated data set for feasibility. The overall results and performance of each approach was compared between the two methods that would assist the decision maker in choosing a suitable solution for their manufacturing line.