Abstract
FUCHIGAMI, H.Y. (2005). Construtive heuristic methods for hybrid flow shop scheduling problem with asymmetric sequence dependent setup times. M. Sc. Dissertation – Escola de Engenharia de Sao Carlos, Universidade de Sao Paulo, Sao Carlos. 2005. This work adressess the hybrid flow shop scheduling problem with asymmetric sequence dependent setup times. This environment of production system is common in graphical, chemical, fabric, paper and ink industries. It’s characterized by systems with large mix of products. Any productive process requires an efficient management by means of Production Planning and Control. This activity includes scheduling, i.e., the resources allocation for the execution of jobs in a time base. Scheduling is one of the tasks most complex in production management, since it deals simultaneously with different types of resources and activities. Moreover, the number of possible solutions grows exponentially in some dimensions, in accordance with the number of jobs, operations or machines, conferring a combinatorial nature to the problem. In the environment studied in this work, the operations of each job are processed in multiple production stages. The number of machines in each stage can be different. Each operation is processed by only one machine in each stage. The setup times have a significant variability in function of the sequence of job processing on the machines. The objective is minimizing the total time to complete the schedule (makespan). Four constructive heuristic methods were developed on the basis of algorithms reported in the literature for solving permutation flow shop and parallel machine problems with sequence dependent setup times. The proposed heuristic methods have been compared between themselves, since no constructive heuristics have been found in the literature for the scheduling problem considered in this work. The focus of the research was the study of the influence of the relations among the range of the times processing and setup times in each method. The statistics used in order to evaluate the heuristic performances were the percentage of success (in finding the best solution), relative deviation, standard deviation of relative deviation and average computation time. Results from computational experience are discussed.
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