Constrained neural approaches to quadratic assignment problems

✍ Scribed by S. Ishii; M. Sato

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 167 KB
• Volume: 11
• Category: Article
• ISSN: 0893-6080
• DOI: 10.1016/s0893-6080(98)00077-x

✦ Synopsis

In this paper, we discuss analog neural approaches to the quadratic assignment problem (QAP). These approaches employ a hard constraints scheme to restrict the domain space, and are able to obtain much improved solutions over conventional neural approaches. Since only a few strong heuristics for QAP have been known to date, our approaches are good alternatives, capable of obtaining fairly good solutions in a short period of time. Some of them can also be applied to large-scale problems, say of size N Ն 300.