Bicriteria scheduling problem for unrelated parallel machines
Computers and Industrial Engineering
Computers and Industrial Engineering
Computers and Industrial Engineering
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Scheduling unrelated parallel machines with sequence-dependent setups
Computers and Operations Research
Application areas of AIS: The past, the present and the future
Applied Soft Computing
International Journal of Computer Applications in Technology
Computers and Industrial Engineering
Computers and Operations Research
Computers and Industrial Engineering
Computers and Industrial Engineering
Computers and Industrial Engineering
Computers and Industrial Engineering
A multi-objective genetic local search algorithm and itsapplication to flowshop scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Mathematical and Computer Modelling: An International Journal
A multiobjective optimization approach to solve a parallel machines scheduling problem
Advances in Artificial Intelligence
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This study presents a novel artificial immune system for solving a multiobjective scheduling problem on parallel machines (MOSP), which has the following characteristics: (1) parallel machines are nonidentical, (2) the type of jobs processed on each machine can be restricted, and (3) the multiobjective scheduling problem includes minimizing the maximum completion time among all the machines (makespan) and minimizing the total earliness/tardiness penalty of all the jobs. In this proposed algorithm, the cells are represented by a vector group, and a local search algorithm is incorporated to facilitate the exploitation of the search space. Specially, a new diversity technique is proposed to preserve the diversity of the population and enhance the exploration of the solution space. Simulation results show the proposed algorithm outperforms the vector immune genetic algorithm (VIGA).