论文信息 - RobustSolutions byusing Evolutionary Computations onDynamicMax-Sat Problems

RobustSolutions byusing Evolutionary Computations onDynamicMax-Sat Problems

Inthis paper, optimization problems suchthat thelandscape oftheobjective function changes overtimeare treated. Conventional approaches forsuchtime-varying functions byusing Evolutionary Computations aredesigned to track moving optimal solutions. Onthecontrary, theproposed method inthis paper tries tofind outstable solutions, i.e., robust solutions, whichmaynotbeoptimal ateachtimestep butexhibit better performance forall timesteps. Suchstable solutions areuseful iftheacquired solutions areoperated byhuman.

Hisashi Handa

[1] Roberto Battiti,et al. Reactive search, a history-sensitive heuristic for MAX-SAT , 1997, JEAL.

[2] Paul A. Viola,et al. MIMIC: Finding Optima by Estimating Probability Densities , 1996, NIPS.

[3] H. Handa,et al. Robust route optimization for gritting/salting trucks: a CERCIA experience , 2006, IEEE Computational Intelligence Magazine.

[4] Jürgen Branke,et al. Evolutionary optimization in uncertain environments-a survey , 2005, IEEE Transactions on Evolutionary Computation.