Priority rules for job shops with weighted tardiness costs
Management Science
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
On Permutation Representations for Scheduling Problems
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Developments from a June 1996 seminar on Online algorithms: the state of the art
Creating Robust Solutions by Means of Evolutionary Algorithms
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Production scheduling and rescheduling with genetic algorithms
Evolutionary Computation
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Dynamic Time-Linkage Problems Revisited
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Optimization of Online Patient Scheduling with Urgencies and Preferences
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Machine scheduling in custom furniture industry through neuro-evolutionary hybridization
Applied Soft Computing
A genetic algorithm for radiotherapy pre-treatment scheduling
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Proposition of selection operation in a genetic algorithm for a job shop rescheduling problem
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Performance evaluation of evolutionary heuristics in dynamic environments
Applied Intelligence
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This contribution addresses the role of anticipation in evolutionary algorithms for dynamic optimization problems. Recent approaches have mainly focused on maintaining the population diversity as a warrant for the ability of tracking the optimum. In our paper, we show that it is also useful to anticipate changes of the environment by explicitly searching for solutions which maintain flexibility. Although this is a valid approach to all dynamic optimization problems, it seems particularly important for optimization problems where a part of the solution is fixed at each step. For the example of job shop scheduling, we suggest a measure of flexibility and show that much better solutions can be obtained when this measure is incorporated into the fitness-function.