Document Type : Original Article


1 Associate Professor, Shahid Beheshti University.

2 M.Sc., Raja Institute of Higher Education.


During the recent decades, flow shop scheduling problem has investigated with different assumptions. One of the most important one that has attracted many researchers, is consideration the concept of learning effect. In real situation of work environment, learning effect is not limited to job position, in other word, workers experiments also should be considered during the process of operations. In one hand, there are factors that can cause machines and equipment unavailability in the planning horizon. This study investigates flow shop scheduling problem with machine availability constraints and learning effect based on a hybrid model. This learning model includes not only job positions but also total logarithmic processing time of jobs. First, a mixed integer liner programming model has been proposed to formulate the problem. Because of high complexity of this model, two meta-heuristic algorithms, simulated annealing (SA) and cloud theory-based simulated annealing (CSA) have been used to find nearly optimal solutions. Finally it is cleared that, CSA could be more successful in generating nearly optimal solutions than SA.


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