Efficient algorithms for scheduling semiconductor burn-in operations
Operations Research
Hashing vectors for tabu search
Annals of Operations Research - Special issue on Tabu search
Minimizing the makespan on a batch machine with non-identical job sizes: an exact procedure
Computers and Operations Research
A hybrid two-stage flowshop with limited waiting time constraints
Computers and Industrial Engineering
The Batch Loading and Scheduling Problem
Operations Research
Minimizing total weighted tardiness on a single batch process machine with incompatible job families
Computers and Operations Research
Scheduling a capacitated batch-processing machine to minimize makespan
Robotics and Computer-Integrated Manufacturing
Computers and Operations Research
Minimizing makespan in a flow shop with two batch-processing machines using simulated annealing
Robotics and Computer-Integrated Manufacturing
Improved MILP models for two-machine flowshop with batch processing machines
Mathematical and Computer Modelling: An International Journal
Mixed integer formulation to minimize makespan in a flow shop with batch processing machines
Mathematical and Computer Modelling: An International Journal
An effective neighborhood search algorithm for scheduling a flow shop of batch processing machines
Computers and Industrial Engineering
Tabu search and lower bounds for a combined production-transportation problem
Computers and Operations Research
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Batch processing machines are frequently encountered in many industrial environments. A batch processing machine is one which can process several jobs simultaneously as a batch. The processing time of a batch is equal to the largest processing time of any job in the batch. This study deals with the problem of scheduling jobs in a flowshop with two batch processing machines such that the makespan is minimized. A heuristic based on Tabu search (TS) technique is proposed. The proposed heuristic is compared with a heuristic based on mixed integer linear programming (MILP). Because the complexity of the MILP-based heuristic is depended on the number of job batches, the comparison is under up-to-eight batches problem. In order to measure the proposed TS-based heuristic in larger batch problem, the relative error percentage with the lower bound (REP"L"B) is used. The results show that the proposed heuristic is efficient and effective for the problems with relative large job sizes.