Outputs (87)

Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails (2010)
Presentation / Conference Contribution
Li, H., Landa-Silva, D., & Gandibleux, X. Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails. Presented at Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010)

Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic representation, called Q-bit, to encode individuals in population. Unlike standard... Read More about Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails.

Towards the design of heuristics by means of self-assembly (2010)
Presentation / Conference Contribution
Terrazas, G., Landa-Silva, D., & Krasnogor, N. Towards the design of heuristics by means of self-assembly. Presented at Developments in Computational Models (DCM 2010)

The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to... Read More about Towards the design of heuristics by means of self-assembly.

Discovering beneficial cooperative structures for the automated construction of heuristics (2010)
Book Chapter
Terrazas, G., Landa-Silva, D., & Krasnogor, N. (2010). Discovering beneficial cooperative structures for the automated construction of heuristics. In Nature inspired cooperative strategies for optimization (NICSO 2010) (89-100). Springer Verlag. https://doi.org/10.1007/978-3-642-12538-6_8

The current research trends on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to... Read More about Discovering beneficial cooperative structures for the automated construction of heuristics.

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.

Heuristic approach for automated shelf space allocation (2009)
Presentation / Conference Contribution
Landa-Silva, D., Marikar, F., & Le, K. (2009, March). Heuristic approach for automated shelf space allocation. Presented at ACM Symposium on Applied Computing, Honolulu, Hawaii

Shelf space allocation is the problem of efficiently arranging retail products on shelves in order to maximise profit, improve stock control, improve customer satisfaction, etc. Most work reported in the literature on this problem has focused on the... Read More about Heuristic approach for automated shelf space allocation.

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.

Great deluge with non-linear decay rate for solving course timetabling problems (2008)
Presentation / Conference Contribution
Landa-Silva, D., & Obit, J. H. (2008, September). Great deluge with non-linear decay rate for solving course timetabling problems. Presented at 2008 4th International IEEE Conference Intelligent Systems, IS 2008, Varna, Bulgaria

Course timetabling is the process of allocating, subject to constraints, limited rooms and timeslots for a set of courses to take place. Usually, in addition to constructing a feasible timetable (all constraints satisfied), there are desirable goals... Read More about Great deluge with non-linear decay rate for solving course timetabling problems.

Evolutionary multi-objective simulated annealing with adaptive and competitive search direction (2008)
Presentation / Conference Contribution
Li, H., & Landa-Silva, D. (2008, June). Evolutionary multi-objective simulated annealing with adaptive and competitive search direction. Presented at 2008 IEEE Congress on Evolutionary Computation, CEC 2008, Hong Kong, China

In this paper, we propose a population-based implementation of simulated annealing to tackle multi-objective optimisation problems, in particular those of combinatorial nature. The proposed algorithm is called Evolutionary Multiobjective Simulated An... Read More about Evolutionary multi-objective simulated annealing with adaptive and competitive search direction.

Adaptive and assortative mating scheme for evolutionary multi-objective algorithms (2008)
Book Chapter
Le, K., & Landa-Silva, D. (2008). Adaptive and assortative mating scheme for evolutionary multi-objective algorithms. In Artificial Evolution: 8th International Conference, Evolution Artificielle, EA 2007, Tours, France, October 29-31, 2007, Revised Selected Papers (172-183). Springer Verlag. https://doi.org/10.1007/978-3-540-79305-2_15

We are interested in the role of restricted mating schemes in the context of evolutionary multi-objective algorithms. In this paper, we propose an adaptive assortative mating scheme that uses similarity in the decision space (genotypic assortative ma... Read More about Adaptive and assortative mating scheme for evolutionary multi-objective algorithms.