MODELOS MATEMÁTICOS PARA OS PROBLEMAS DE DIMENSIONAMENTO E PROGRAMAÇÃO DE BATELADAS EM MÁQUINA ÚNICA E MÁQUINAS PARALELAS
TRINDADE, Renan Spencer. MATHEMATICAL MODELS FOR SCHEDULING A SINGLE AND PARALLEL IDENTICALS BATCH PROCESSING MACHINES WITH NON-IDENTICAL JOB SIZES. 2014. 100 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Santa Maria, Santa Maria, 2014.
Trindade, Renan Spencer
Problems of scheduling on batch processing machines to minimize makespan are widely exploited by academic literature, mainly motivated by reliability testing in the semiconductor industry. These problems consist in grouping jobs as a batch and scheduling the processing in single or parallel machines. The jobs have non-identical processing times and non-identical sizes and the total size of the batch cannot exceed the machine capacity. The processing time of a batch is given by the longest processing time of any job in the batch. Jobs with nonidentical release times can also be considered, and in this case a batch can only be processed after the job with the longest release time in the batch is available. We consider four different problems of scheduling on batch processing machines with non-identical job size and different characteristics: single batch processing machine (1|sj,B|Cmax), single batch processing machine with non-identical job release times (1|rj,sj,B|Cmax), identical parallel batch processing machines (Pm|sj,B|Cmax), and identical parallel batch processing machines with non-identical job release times (Pm|rj,sj,B|Cmax). New mathematical models are proposed with formulations that exploit characteristics of each problem. The mathematical models are solved using CPLEX and the computational results show that the proposed models performed better than other models from literature. The new models for 1|sj,B|Cmax and 1|rj,sj,B|Cmax are compared with previously published meta-heuristics and the results show that the models provide better solutions than meta-heuristics methods with competitive computational times.