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Interdisciplinary research experience in multiagent systems, swarm intelligence, and meta-heuristics, including general frameworks and problem-specific search/optimization and scheduling/planning strategies, and decentralized coordination mechanisms, for efficiently solving hard computational problems and distributed real-world complex problems.

  • Metaheuristic Frameworks: Multiagent Optimization System (MAOS)
  • Optimization Problems: Travelling Salesman Problem (TSP), Quadratic Knapsack Problem (QKP), Graph Coloring Problem (GCP), Flow-Shop Scheduling Problem (FSP), Quadratic Assignment Problem (QAP), Numerical Optimization Problem (NOP)
  • Natural-Inspired Algorithms: Particle Swarm Optimisation (PSO), Differential Evolution (DE), DEPSO, Social Cognitive Optimization (SCO)
  • Real-World Applications: Intelligent Transportation Systems, Business Process Management; Technology CAD; Engineering Optimization

    • Maintained by AdaptiveBox StUdIo, under a Creative Commons Attribution 3.0 License.