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- Simon Huband, Philip Hingston, Luigi Barone, R. Lyndon While
- IEEE Trans. Evolutionary Computation
- 2006

When attempting to better understand the strengths and weaknesses of an algorithm, it is important to have a strong understanding of the problem at hand. This is true for the field of multiobjective evolutionary algorithms (EAs) as it is for any other field. Many of the multiobjective test problems employed in the EA literature have not been rigorously… (More)

- Mohammad Reza Bonyadi, Zbigniew Michalewicz, Luigi Barone
- IEEE Congress on Evolutionary Computation
- 2013

There are some questions concerning the applicability of meta-heuristic methods for real-world problems; further, some researchers claim there is a growing gap between research and practice in this area. The reason is that the complexity of real-world problems is growing very fast (e.g. due to globalisation), while researchers experiment with benchmark… (More)

- R. Lyndon While, Lucas Bradstreet, Luigi Barone
- IEEE Trans. Evolutionary Computation
- 2012

We describe a new algorithm WFG for calculating hypervolume exactly. WFG is based on the recently-described observation that the exclusive hypervolume of a point p relative to a set S is equal to the difference between the inclusive hypervolume of p and the hypervolume of S with each point limited by the objective values in p. WFG applies this technique… (More)

- Luigi Barone
- 1999

Evolution is the process of adapting to a potentially dynamic environment. By utilising the implicit learning characteristic of evolution in our algorithms, we can create computer programs that learn, and evolve, in uncertain environments. We propose to use evolutionary algorithms to learn to play games of imperfect information – in particular, the game of… (More)

- R. Lyndon While, Philip Hingston, Luigi Barone, Simon Huband
- IEEE Trans. Evolutionary Computation
- 2006

We present an algorithm for calculating hypervolume exactly, the Hypervolume by Slicing Objectives (HSO) algorithm, that is faster than any that has previously been published. HSO processes objectives instead of points, an idea that has been considered before but that has never been properly evaluated in the literature. We show that both previously studied… (More)

- Anthony Di Pietro, R. Lyndon While, Luigi Barone
- IEEE Congress on Evolutionary Computation
- 2004

For many “real world” applications of evolutionary computation, the fitness function is obscured by random noise. This interferes with the evaluation and selection process and adversely affects the performance of the algorithm. We present a study of noise compensation techniques designed to better counteract the negative effects of noise. We introduce… (More)

- Luigi Barone, R. Lyndon While
- GECCO
- 2000

- Lucas Bradstreet, R. Lyndon While, Luigi Barone
- IEEE Trans. Evolutionary Computation
- 2008

When hypervolume is used as part of the selection or archiving process in a multi-objective evolutionary algorithm (MOEA), it is necessary to determine which solutions contribute the least hypervolume to a front. Little focus has been placed on algorithms that quickly determine these solutions and there are no fast algorithms designed specifically for this… (More)

- Simon Huband, Luigi Barone
- 2003

Evolutionary algorithms have been applied with great success to the difficult field of multi-objective optimisation. Nevertheless, the need for improvements in this field is still strong. We present a new evolutionary algorithm, ESP (the Evolution Strategy with Probabilistic mutation). ESP extends traditional evolution strategies in two principal ways: it… (More)