achieves the searching not only globally, but also locally. To keep general purpose, self-control processing by a handshake system is introduced. By adopting the handshake system, the proposed architecture can be applied to various combinatorial optimization problems by only changing an encoder, a decoder, and an evaluation circuit. Furthermore, the proposed architecture realizes flexibility fo...

Ž . The World-Wide Web WWW based Internet services have become a major channel for information delivery. For the same reason, information overload also has become a serious problem to the users of such services. It has been estimated that the amount of information stored on the Internet doubled every 18 months. The speed of increase of homepages can be even faster, some people estimated that it...

We present a new approach to the concrete planning (CP) shown to be a NP-hard problem [7]. This is the third stage of Web service composition (WSC) in the PlanICS framework [1]. The first two phases, namely an abstract planning and offer collecting, basing on an ontology, a user query, and a service registry provide data necessary for CP. A new hybrid algorithm (HSA), which combines Simulated A...

In this paper, we present a hybrid method combining Tabu Search (TS) optimization algorithm with the Very Fast Simulated Annealing (VFSA) procedure for the Job-shop Scheduling Problem (JSP). Tabu search algorithms are among the most effective approaches for solving the job shop scheduling problem which is one of the most difficult NP-complete problems. However, neighborhood structures and move ...

Two well known stochastic optimization algorithms, simulated annealing and genetic algorithm are compared when using a sample to minimize an objective function which is the expectation of a random variable. Since they lead to minimum depending on the sample, a weighted version of simulated annealing is proposed in order to reduce this kind of overt bias. The algorithms are implemented on an opt...

Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. Therefore, reducing computational cost and providing quick feedback at intermediate s...

Many significant engineering and scientific problems involve optimization of some criteria over a combinatorial configuration space. The two methods most often used to solve these problems effectively—simulated annealing (SA) and genetic algorithms (GA)—do not easily lend themselves to massive parallel implementations. Simulated annealing is a naturally serial algorithm, while GA involves a sel...

Bayesian belief networks (BBN’s) are a popular graphical representation for reasoning under (probabilistic) uncertainty. An important, and NP-complete, problem on BBN’s is the maximum a posteriori (MAP) assignment problem, in which the goal is find the network assignment with highest conditional probability given a set of observances, or evidence. In this paper, we present an adaptive hybrid te...

This paper proposes a new hybrid approach which combines simulated annealing and standard backpropagation for optimizing Multi Layer Perceptron Neural Networks (MLP) for time series prediction. Experimental tests were carried out on four simulated series with known features and on the Sunspot series. The results have shown that this approach selects the appropriate time series lags and builds a...