Sequencing with earliness and tardiness penalties: a review
Operations Research
Linear network optimization: algorithms and codes
Linear network optimization: algorithms and codes
Scheduling in Computer and Manufacturing Systems
Scheduling in Computer and Manufacturing Systems
Algorithms for Network Programming
Algorithms for Network Programming
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Computers and Industrial Engineering
A meta-heuristic approach to solve a JIT scheduling problem in hybrid flow shop
Engineering Applications of Artificial Intelligence
A two-phase dynamic dispatching approach to semiconductor wafer testing
Robotics and Computer-Integrated Manufacturing
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
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This research considers the problem of scheduling jobs on parallel machines with noncommon due dates and additional resource constraints. The objective is to minimize the total absolute deviation of job completion times about the corresponding due dates. All job processing times are assumed to be the same. This problem is motivated by restrictions that occur in the handling and processing of jobs in certain phases of semiconductor manufacturing and other production systems. We examine two special cases. For the first of these, the number of additional resource types and the resource requirements per job are arbitrary. The problem is formulated as a zero-one integer linear program and the Lagrangian relaxation approach is used to obtain tight lower bounds. In the second case, there exist one single type of additional resource and the resource requirements per job are zero or one. This problem is shown to be equivalent to the asymmetric assignment problem.