It all runs like clockwork with lazy science

Airline crew schedules, train timetables, water usage allocation and hospital staff rosters are just some of the things that present society with mathematical challenges each day. And finding the best solution to these real life situations is now easier thanks to a software platform created by Professor Peter Stuckey from the Department of Computer Science and Software Engineering at the University of Melbourne and NICTA. Dubbed a 'lazy' problem solver, the software platform - which this week won the inaugural Google Australia Eureka Prize for Innovation in Computer Science - creates an effective way for finding the best solution to any problem with numerous possible outcomes. Professor Stuckey says there are two main approaches to solving such problems; constraint programming, and satisfiability programming. The basic premise behind Professor Stuckey's development is to combine the two approaches; so as to make up for the shortcomings in each.lazy ?The problem with constraint solving systems is that they are bad at learning from mistakes made during the search process. On the other hand, satisfiability solvers are very effective at learning from mistakes. The trick is to pass on the inferences made by the constraint program to the satisfiability program, which can then learn automatically,? he says.