Batching and scheduling jobs on batch and discrete processors
Operations Research
Efficient algorithms for scheduling semiconductor burn-in operations
Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Makespan minimization for flow-shop problems with transportation times and a single robot
Discrete Applied Mathematics - Special issue on the combinatorial optimization symposium
Design and Analysis of Experiments
Design and Analysis of Experiments
Computers and Industrial Engineering
Genetic algorithms for a two-agent single-machine problem with release time
Applied Soft Computing
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This paper studies the minimization of makespan in a three-machine flowshop scheduling problem in which a batch processing machine is located between two single processing machines on first and third stages. In this study also transportation capacity and transportation among machines times are explicitly considered. We establish a mixed integer programming model and propose a heuristic algorithm based on the basic idea of Johnson's algorithm. Since the problem under study is NP-hard, a genetic algorithm is also proposed to minimize makespan. The effectiveness of our solution procedures is evaluated through computational experiments. The results obtained from the computational study have shown that the genetic algorithm is a viable and effective approach that is capable to produce consistently good results.