A multi-objective optimization scheme for transportation planning is described. Multi-criteria analysis provides a major advantage in its ability to take into account a range of different, often unrelated criteria, even if these criteria cannot be directly related to quantitative outcome measures. The approach described is specifically addressed to public transportation networks but it is also ...

Vehicle drivetrains are complex integrated systems, which need to be designed for numerous thermodynamic, economic and environmental factors. As part of a project of the Alliance for Global Sustainability between the MIT, the SFITs and the University of Tokyo, a new evolutionary multi-objective optimisation algorithm has been developed and applied to various problems including vehicle drivetrai...

Encoding is a fundamental part of any EA. The solution encoding, and its interactions with the EA’s operators, should be designed to minimise arbitrary search bias. A multidimensional encoding suitable for fully specified fuzzy logic rulebases is investigated, and is shown to have better convergence than traditional single-dimensional encoding. By comparison with 2-point and uniform crossover, ...

Information access tasks involve setting a large number of model parameters (such as term weighting functions or the particular terms from the document collection to use in the model); in addition, information access tasks frequently attempt to satisfy multiple competing objectives, such as precision and recall. We investigate the use of multi-objective evolutionary algorithms for finding model...

Evolutionary relationships among species are usually (i) illustrated by means of a phylogenetic tree and (ii) inferred by optimising some measure of fitness, such as the total evolutionary distance between species or the likelihood of the tree (given a model of the evolutionary process and a data set). The combinatorial complexity of inferring the topology of the best tree makes phylogenetic in...

In this paper we explore established methods for optimising multi-objective functions whilst addressing the problem of preliminary design. Methods from the literature are investigated and new ones introduced. All methods are evaluated within a collaborative project with British Aerospace for whole system airframe design and the basic problems and difficulties of preliminary design methodology a...

It is well known that, on the one hand, combinatorial optimization (CO) provides a powerful tool to formulate and model many optimization problems, on the other hand, a multi-objective (MO) approach is often a realistic and efficient way to treat many real world applications. Nevertheless, until recently, Multi-Objective Combinatorial Optimization (MOCO) did not receive much attention in spite ...

Regression testing is the process of retesting a system after it or its environment has changed. Many techniques aim to find the cheapest subset of the regression test suite that achieves full coverage. More recently, it has been observed that the tester might want to have a range of solutions providing different trade-offs between cost and one or more forms of coverage, this being a multi-obje...