Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Annals of Operations Research
Scheduling about a common due date with earliness and tardiness penalties
Computers and Operations Research
Sequencing with earliness and tardiness penalties: a review
Operations Research
Journal of Computational Physics
Scheduling parallel machines to minimize total weighted and unweighted tardiness
Computers and Operations Research
Parallel machine scheduling with earliness and tardiness penalties
Computers and Operations Research
Mathematical and Computer Modelling: An International Journal
Equivalence of mean flow time problems and mean absolute deviation problems
Operations Research Letters
Computers and Operations Research
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
Computers and Operations Research
Computers and Operations Research
GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
A new inter-island genetic operator for optimization problems with block properties
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Mathematical and Computer Modelling: An International Journal
Improving Grid Resource Usage: Metrics for Measuring Fragmentation
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
On the Improvement of Grid Resource Utilization: Preventive and Reactive Rescheduling Approaches
Journal of Grid Computing
A multi-agent system for the weighted earliness tardiness parallel machine problem
Computers and Operations Research
Journal of Intelligent Manufacturing
Electronic Notes in Theoretical Computer Science (ENTCS)
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This paper considers a scheduling problem where each of n jobs has to be processed without interruption on exactly one of m unrelated parallel machines. For each job, a release date and the processing times on each machine are given, and a common due date d is given for all jobs. The objective is to distribute the jobs to the machines and to schedule the jobs assigned to each machine such that the weighted sum of linear earliness and tardiness penalties is minimal. For this problem, we derive some structural properties useful in connection with the search for an approximate solution. Furthermore, we present various constructive and iterative heuristic algorithms which are compared on problems with up to 500 jobs and 20 machines.