This paper studies the generalized normal distribution algorithm (GNDO) performance for tackling permutation flow shop scheduling problem (PFSSP). Because PFSSP is a discrete and GNDO generates continuous values, largest ranked value rule used to convert those values into ones make applicable solving this problem. Additionally, effectively integrated with local search strategy improve quality o...

In this research, a new approach for tackling the permutation flow shop scheduling problem (PFSSP) is proposed. This algorithm based on steps of elitism continuous genetic improved by two strategies and used largest rank value (LRV) rule to transform values into discrete ones enabling solving combinatorial PFSSP. The first strategy combining arithmetic crossover with uniform give high capabilit...

We propose a constructive heuristic approach for the solution of the permutation flow-shop problem. The objective function of all algorithms is the minimization of the makespan. Our approach employs Johnson’s rule to give a good initial solution for the improvement heuristic, also known as metaheuristics. The proposed heuristic algorithm, named MOD, is tested against four other heuristics that ...