Application of heuristic techniques
Researchers
- Val Lowndes
- Stuart Berry
- Bruce Wiggins
This is concerned with evaluating the strengths and weaknesses of the use of these techniques in problem solving, exploring hybrids that aim to minimise their weaknesses and maximise their strengths. Investigating their application to Goal Programming and multi objective optimisation problems. A range of heuristic techniques, for example Genetic Algorithms, Tabu Search, and Fuzzy Logic have been applied to a range of problems.
Solved problems
Heat flow problems
The aim was to determine the steady state temperature along a metal plate. This problem was solved using Genetic Algorithms and Tabu Search methodologies producing an effective and efficient optimiser (minimising error).
Diet problems
The aim was to produce a set of varied diets thus introducing taste (by variety) into a diet. This problem was solved using Genetic Algorithms and Fuzzy Logic methodologies, producing an effective and efficient optimiser (producing many alternative diets). Effectively solving a multi criteria Goal Programming problem.
Optimising sound reproduction
The aim was to determine a set of speaker settings so that the reproduced sound would replicate the original sound. This problem was solved using Tabu Search methodology producing settings which gave true sound reproduction and improved on currently-used analytically based methods.
Generating production plans
Fuzzy logic was used to carry out a multi-criteria optimisation. Jobs were scheduled so that a set of performance criteria, meeting due dates and optimising customer satisfaction, could be optimised simultaneously.
