Navigating the wilds of industrial optimisation
The continual search for solutions that are better, faster and more efficient is second nature to all engineers. This activity is known as optimisation. But industrial optimisation problems are like the mythical beast, the Jabberwocky; they are big, complex, mean, ill-tempered, and prickly. What is interesting though is how we arrive at optimal solutions; how we can rapidly discard non-contenders, reduce the search-space, and accelerate the passage to the optimum. Essentially how do we optimise the optimisation process? This paper reviews the recent developments in large-scale optimisation algorithms that are suitable for industrial problems. The important issues of correctly formulating the optimisation problem, judging when to add constraints, when to introduce binary variables, and which of the many numerical algorithms to choose are also highlighted with many actual industrial examples such as trajectory planning of the Waiheke ferry, to the optimal operation of steam utility boiler systems, to optimal design of microwave cavities, and the classification of the electrical power usage of suburbs from Dargaville to Wellsford. The take home message is this: With the right tools (many of which are free!), all the world’s problems start to look like optimisation problems where even a slightly better solution is better than nothing at all.