All Outputs (5)

New crossover operators for timetabling with evolutionary algorithms. (2004)
Presentation / Conference Contribution
Lewis, R. M. R., & Paechter, B. (2004). New crossover operators for timetabling with evolutionary algorithms. In A. Lotfi (Ed.), 5th International Conference on Recent Advances in Soft Computing (189-195)

When using an evolutionary algorithm (EA) to optimise a population of feasible course timetables, it is important that the mutation and crossover operators are designed in such a way so that they don?t produce unfeasible or illegal offspring. In this... Read More about New crossover operators for timetabling with evolutionary algorithms..

A memetic algorithm for the university course timetabling. (2004)
Book Chapter
Rossi-Doria, O., & Paechter, B. (2004). A memetic algorithm for the university course timetabling. In CO2004 Book of Abstracts (56). Lancaster University

Solving vehicle routing problems using different multiple ant colony systems. (2004)
Presentation / Conference Contribution
Sa'adah, S., Ross, P., & Paechter, B. (2004). Solving vehicle routing problems using different multiple ant colony systems.

PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation (2004)
Journal Article
de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B., & Martin, J. M. (2004). PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing, 30(5-6), 721-739. https://doi.org/10.1016/j.parco.2003.12.

This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisation problems. We propose a new algorithm called PSFGA (parallel single fron... Read More about PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation.

Improving vehicle routing using a customer waiting time colony. (2004)
Presentation / Conference Contribution
Sa'adah, S., Ross, P., & Paechter, B. (2004). Improving vehicle routing using a customer waiting time colony. In J. Gottlieb, & G. Raidl (Eds.), Evolutionary Computation in Combinatorial Optimization (188-198). https://doi.org/10.1007/978-3-540-24652-7_19

In the vehicle routing problem with time windows (VRPTW), there are two main objectives. The primary objective is to reduce the number of vehicles, the secondary one is to minimise the total distance travelled by all vehicles. This paper describes so... Read More about Improving vehicle routing using a customer waiting time colony..