The single machine early/tardy problem
Management Science
The ant colony optimization meta-heuristic
New ideas in optimization
An ACO algorithm for the shortest common supersequence problem
New ideas in optimization
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An Ant Algorithm with a New Pheromone Evaluation Rule for Total Tardiness Problems
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Ant Colony Optimization for the Total Weighted Tardiness Problem
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling the dynamics of ant colony optimization
Evolutionary Computation
Modelling ACO: Composed Permutation Problems
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Hardware-oriented ant colony optimization
Journal of Systems Architecture: the EUROMICRO Journal
Expert Systems with Applications: An International Journal
A Multiobjective Resource-Constrained Project-Scheduling Problem
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Dynamic optimization of a heterogeneous swarm of robots
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
Multi-constraint system scheduling using dynamic and delay ant colony system
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
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A new approach for solving permutation scheduling problems with Ant Colony Optimization is proposed in this paper. The approach assumes that no precedence constraints between the jobs have to be fulfilled. It is tested with an ant algorithm for the Single Machine Total Weighted Deviation Problem. The new approach uses ants that allocate the places in the schedule not sequentially, as the standard approach, but in random order. This leads to a better utilization of the pheromone information. It is shown that adequate combinations between the standard approach which can profit from list scheduling heuristics and the new approach perform particularly well.