The pick-up operation of steel plates in a shipyard is a process to select the required steel plates from the stockyard based on the production plan of the shipyard. Two major factors are considered in evaluating the optimization algorithms for steel plate pick-up operation scheduling. The first is the effectiveness of the algorithm result, which means that the pick-up operation plan can meet the requirement of minimization of operation cost or time. The second is the efficiency of the algorithm execution. Since the steel plate pick-up operation is a daily routine with heavy workload, the execution of algorithm should be practiced in a very limited time. In recent years, the parallel computing technology has developed rapidly. Parallel computing refers to a form of computation where many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into numerous smaller ones. A parallel multi-layer genetic algorithm was designed based on the analysis of the present nested algorithm, and some key problems in parallel algorithm implementation were solved. An experimental example was illustrated. The results showed that the speedup of the proposed parallel algorithm comes up to 3.144 on a computer with quad-core processer and the total execution time is shortened greatly. The parallel nested genetic algorithm can meet the requirement for actual operation period.
A parallel optimization algorithm for steel plate pick-up operation scheduling problem
International Journal of Simulation Modelling ; 13 , 3 ; 323-334
2014
12 Seiten, Bilder, Tabellen, 14 Quellen
Aufsatz (Zeitschrift)
Englisch
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