Selected heuristic algorithms for solving job shop and flow shop scheduling problems

Abstract

Importance of job shop and flow shop scheduling has increased to a high extent. Nowadays, each and every industry focuses largely on how to schedule their machine working, since it is an important factor which decides the net productivity. All manufacturing systems including flexible manufacturing system follow a planned schedule of machine operation depending on the demand criterion. With the increase in number of machines and jobs to be scheduled, complexity of the problem increases which demands the need of a proper scheduling technique. Here this thesis shows some of the essential methods of solving a job shop and flow shop scheduling problems. This thesis focuses on finding the most efficient way of scheduling in a flow shop environment with the help of heuristics algorithms that include Palmer’s algorithm, CDS algorithm and NEH algorithm. Comparison was also done between the various heuristics algorithms. For getting the optimum make span for job shop scheduling we have used branch and bound algorithm and shifting bottleneck algorithm. Basis input parameters are given in the problem which are then used for computing the make span. A C programming code was generated to find the optimum results of the scheduling problem.