Using Multi-chromosomes to Solve a Simple Mixed Integer Problem (1997) [4 citations — 0 self]
by Hans J. Pierrot, Robert Hinterding
Australian Joint Conference on Artificial Intelligence
ftp://matilda.vut.edu.au/pub/papers/rhh/mip.ps
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Abstract:
Abstract. Multi-chromosomes representations have been used in Genetic Algorithms to decompose complex solution representations into simpler components each of which is represented onto a single chromosome. This paper investigates the effects of distributing similar structures over a number of chromosomes. The solution representation of a simple mixed integer problem is encoded onto one, two, or three chromosomes to measure the effects. Initial results showed large differences, but further investigation showed that most of the differences were due to increased mutation, but multi-chromosome representation can give superior results. 1
Citations
| 48 | 1994�. Constrained Optimization via Genetic Algorithms – Lai, Qi |
| 16 | A multi-chromosome genetic algorithm for pallet loading – Juliff - 1993 |
| 7 | Self-adaptation using multi-chromosomes – Hinterding - 1997 |
| 5 | A genetic algorithm for stock cutting: an exploration of mapping schemes – Hinterding, Juliff - 1993 |
| 1 | An investigation of Multi-chromosome Genetic Algorithms – Pierrot - 1997 |
