Turnpike optimality of Smith's Rule in parallel machines stochastic scheduling
Mathematics of Operations Research
Multi machine scheduling: an agent-based approach
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Sequencing Tasks with Exponential Service Times to Minimize the Expected Flow Time or Makespan
Journal of the ACM (JACM)
Approximation in stochastic scheduling: the power of LP-based priority policies
Journal of the ACM (JACM)
Simulation with Arena
Scheduling unrelated parallel machines to minimize total weighted tardiness
Computers and Operations Research
Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines
Computers and Operations Research
Simulation-based multi-objective optimization of a real-world scheduling problem
Proceedings of the 38th conference on Winter simulation
Proceedings of the 2007 Summer Computer Simulation Conference
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This paper addresses the problem of batch scheduling in an unrelated parallel machine environment with sequence dependent setup times and an objective of minimizing the weighted mean completion time. Identical jobs are batched together and are available at time zero. Processing time of each job of a batch is determined according to both the machine it will be assigned to and the batch group to which the job belongs. The jobs' processing times and setup times are stochastic for better depiction of the real world. This is a NP-hard problem and in this paper, a solution heuristic is developed and compared to existing ones using simulation. The results and analysis obtained from the computational experiments proved the superiority of the proposed algorithm PMWP over the other algorithms presented.