While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yora...
—A dramatic and continuous increase in the complexity and size of websites on the Internet makes rather difficult to build such websites with required information to be easily fo...
Abstract. In this paper, we present a constraint-partitioning approach for finding local optimal solutions of large-scale mixed-integer nonlinear programming problems (MINLPs). Ba...
In this paper we investigate how “self-awareness'', through on-line self-monitoring and measurement, coupled with intelligent adaptive behaviour in response to observe...