Modified heuristic algorithms for scheduling multiple batch processors with incompatible job families

This paper considers the problem of scheduling parallel nonidentical batch processors in the presence of dynamic job arrivals with incompatible job-families and nonidentical job sizes to maximize the utilization of the batch processors. Four modified heuristic algorithms are provided. A series of computational experiments are carried out and it is shown that (1) all the algorithms are capable of obtaining best result and perform better than the benchmark procedure; (2) there is no influence of the job-size distribution on the performance of these algorithms; but (3) changing job-family processing time and job-size distribution together does influence the performance of the algorithm. Further, from the computational experiment it is concluded that all the proposed algorithms are capable of solving problems with more than 1000 jobs in an extremely low computational time. It is also seen that the total computational time for all the algorithms together is very low. It is in fact practical to run within a short time all the algorithms on a particular instance, and to take the best solutions by combining the good points of all these algorithm