Computer models are needed to represent transport flows, where people choose to live and work in cities – in order to create the most effective investment plans, for instance for major transport projects. Entropy-maximising models have produced a powerful way of doing this and revolutionised the field.
A major challenge of effective planning for cities and other human communities is that they are complex systems that evolve organically - at least as much from individual and small group decisions as from organised ‘top-down’ planning.
In 1957 physics professor Edwin T. Jaynes used the principle of 'maximum entropy' to estimate the probable distribution of information in a system. The principle was introduced into urban studies by Alan Wilson in 1970, in his book Entropy in Urban and Regional Modeling. He used transport models to estimate urban transport in a maximum entropy environment – taking account not only of physical, but also economic and social constraints.
These models have been influential in urban planning, from public transport networks to retail locations, and are still used widely in geography and transport planning.