We consider the problem of sequencing jobs on a single machine while minimizing a nondecreasing function of two criteria. We develop a heuristic procedure that quickly finds a good solution for bicriteria scheduling. The procedure is based on using several arcs in the criterion space that are repres
A mixed evolutionary/heuristic approach to shape optimization
β Scribed by R. Le Riche; G. Cailletaud
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 380 KB
- Volume
- 41
- Category
- Article
- ISSN
- 0029-5981
No coin nor oath required. For personal study only.
β¦ Synopsis
The problem of ΓΏnding the optimal shape of a continuous structure is addressed using, alternatively, heuristic, evolutionary and mixed evolutionary and heuristic optimization strategies. Boundaries are represented by B-splines. Two heuristics for minimizing the weight of a structure subject to limits on von Mises stresses and geometrical constraints are implemented: 'generalized biological growth' and 'penalized biological growth'. Penalized biological growth adds to generalized biological growth a control for shape changes. This control is based on the overall state of constraints satisfaction in the structure. The two heuristics are very e cient at improving the designs, but they do not yield globally optimal shapes. Therefore, they are interfaced with an evolutionary optimizer. Di erent strategies for mixing evolutionary search and biological growth are compared. Results are obtained for fan disk shape problems. They show that mixing evolutionary search with biological growth improves the e ciency of the optimization. The method o ers to the designer new paths for a better component determination. ?
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