A Rosetta stone for connectionism
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Genetic Algorithms and the Immune System
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Mining Association Rules in Preference-Ordered Data
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Grid resource management: state of the art and future trends
Grid resource management: state of the art and future trends
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
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In this paper, an improved negative selection procedure to handle constraints in a multi-criterion evolutionary algorithm has been proposed. The problem that is of interest to us is the complex task assignment for a distributed computer system. Both a workload of a bottleneck computer and the cost of system are minimized; in contrast, a reliability of the system is maximized. Moreover, constraints related to memory limits and computer locations are imposed. Finally, an evolutionary algorithm with tabu search procedure and the improved negative selection is proposed to provide effective solutions.