Batching and scheduling jobs on batch and discrete processors
Operations Research
Efficient algorithms for scheduling semiconductor burn-in operations
Operations Research
Minimizing makespan for multi-spindle head machines with a mobile table
Computers and Operations Research
A Two-Stage Flexible Flowshop Problem with Deterioration
COCOON '08 Proceedings of the 14th annual international conference on Computing and Combinatorics
Minimizing makespan in a flow shop with two batch-processing machines using simulated annealing
Robotics and Computer-Integrated Manufacturing
Computers and Industrial Engineering
Computers and Operations Research
Computers and Industrial Engineering
Two-stage hybrid flow shop scheduling with dynamic job arrivals
Computers and Operations Research
Enhanced mixed integer programming model for a transfer line design problem
Computers and Industrial Engineering
Minimizing makespan in a two-machine flowshop scheduling with batching and release time
Mathematical and Computer Modelling: An International Journal
Tabu search and lower bounds for a combined production-transportation problem
Computers and Operations Research
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This paper considers a scheduling problem for a two-machine flowshop where a discrete processing machine is followed by a batch processing machine and a finite number of jobs arrive dynamically at the first machine. In the flowshop, the discrete processing machine processes one job at a time and the batch processing machine processes a batch of jobs simultaneously. The objective is to find the optimal schedule which minimizes the maximum completion time (makespan) of all jobs. In the situation where preemption is allowed on the discrete processing machine, it is shown that the optimal schedule can be found in polynomial time. However, in the situation where no preemption is allowed on the discrete processing machine, it is shown that the problem is NP-complete, for which an efficient heuristic solution algorithm is constructed and its tight worst-case error bound is derived. Numerical experiments show that the heuristic algorithm consistently generates good schedules.