All Outputs (3)

An improved version of volume dominance for multi-objective optimisation (2009)
Book Chapter
Le, K., Landa-Silva, D., & Li, H. (2009). An improved version of volume dominance for multi-objective optimisation. In Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings (231-245). Springer Verlag. https://doi.org/10.1007/978-3-642-01020-0_21

This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volume dominance on the performance of multi-objective evolutionary algorithms is inve... Read More about An improved version of volume dominance for multi-objective optimisation.

Evolutionary non-linear great deluge for university course timetabling (2009)
Book Chapter
Landa-Silva, D., & Obit, J. H. (2009). Evolutionary non-linear great deluge for university course timetabling. In Hybrid Artificial Intelligence Systems: 4th International Conference, HAIS 2009, Salamanca, Spain, June 10-12, 2009. Proceedings (269-276). Springer Verlag. https://doi.org/10.1007/978-3-642-02319-4_32

This paper presents a hybrid evolutionary algorithm to tackle university course timetabling problems. The proposed approach is an extension of a non-linear great deluge algorithm in which evolutionary operators are incorporated. First, we generate a... Read More about Evolutionary non-linear great deluge for university course timetabling.

Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach (2009)
Book Chapter
Castro, J. P., Landa-Silva, D., & Moreno Pérez, J. A. (2009). Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2008) (103-114). Springer Verlag. https://doi.org/10.1007/978-3-642-03211-0_9

This paper investigates the ability of a discrete particle swarm optimization algorithm (DPSO) to evolve solutions from infeasibility to feasibility for the Vehicle Routing Problem with Time Windows (VRPTW). The proposed algorithm incorporates some p... Read More about Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach.