Genetic State-Space Search for Constrained Optimization Problems

This paper introduces GSSS (Genetic State-Space Search). The integration of two general search paradigms — genetic search and state-space-search provides a general framework which can be applied to a large variety of search problems. Here, we show how GSSS solves constrained optimization problems (COPs). Basically, it searches for "promising search states" from which good solutions can be easily found. Domain knowledge in the form of constraints is used to limit the space to be searched. Interestingly, our approach allows the handling of constraints within genetic search at a general domain independent level. First, we introduce a genetic representation of search states. Next, we provide empirical results

• Type: Conference
• Year: 1993
• Where: IJCAI
• Authors: Jan Paredis
• Keywords: Genetic Search, Genetic State-Space Search, IJCAI 1993, IJCAI 2007, Search States