Solving Permutation Flow shop Problem by the Regulations of Columnar Entries in the Processing Times Matrix

Scheduling theory and permutation therein are two important subjects in discrete operation research. In this paper, a new heuristic algorithm is proposed for solving permutation flow shop problem by using regulations of columnar entries in the processing times matrix. There are  jobs to be processed on  machines with deterministic processing times and the object is obtaining the minimum of the total time to complete the schedule (makespan). This is not solvable in polynomial time. First, an initial suitable sequence of jobs is determined similar to many heuristics. For this, the matrix  is made such that every determines the measure of the fitness for the location of the th old row in the th new position. Thereafter, the Bellman Esogbue Nabeshima theorem is used. The presented algorithm is compared with the NEH (the best well-known existing method). This comparison is made by the Taillard’s standard test problems. Computational results demonstrate that the heuristic algorithm is better than some of the proposed heuristics known so far and it is superior with respect to others in a number of Taillard instances. As a result, it is almost as good as NEH and is very promising for the problem. On the basis of the structure of the proposed algorithm, it can perform a role as meta-heuristic.