The combination of the broad problem searching capabilities of a genetic algorithm with the local maxima location capabilities of a hill climbing algorithm can be a powerful technique for solving classification problems. Producing a number of specialist artificial neural networks, each an expert on one category, can be beneficial when solving problems in which the categories are distinct. This ...

Constructive multi-start search algorithms are commonly used to address combinatorial optimization problems. Multi-start algorithms recover from local optima by restarting, which can lead to redundant configurations when search paths converge. In this paper, we investigate ways to minimize redundancy using record keeping and analyze several restart algorithms in the context of iterative hill cl...

In the present paper we introduce new heuristic methods for the state minimization of nondeterministic finite automata. These methods are based on the classical Kameda-Weiner algorithm joined with local search heuristics, such as stochastic hill climbing and simulated annealing. The description of the proposed methods is given and the results of the numerical experiments are provided.

Simulated annealing is a general optimisation algorithm, based on hill-climbing. As in hill-climbing, new candidate solutions are selected from the ‘neighbourhood’ of the current solution. For continuous parameter optimisation, it is practically impossible to choose direct neighbours, because of the vast number of points in the search space. In this case, it is necessary to choose new candidate...

The problem of programming an artificial ant to follow the Santa Fe trail is used as an example program search space. Previously reported genetic programming, simulated annealing and hill climbing performance is shown not to be much better than random search on the Ant problem. Enumeration of a small fraction of the total search space and random sampling characterise it as rugged with multiple ...

Abstract—In search-based graph drawing methods there are typically a number of parameters that control the search algorithm. These parameters do not affect the fitness function, but nevertheless have an impact on the final layout. One such search method is hill climbing, and, in the context of schematic layout, we explore how varying three parameters (grid spacing, the starting distance of allo...

| Classical test functions known as F1 to F10 are often used as a benchmark for heuristic optimisation techniques. Recently it has been remarked in literature that relying on the results obtained for their optimisation may be improper or even misleading to assess the eeciency of a technique with respect to others, and a method for developing new more reliable test functions has been given. In t...

This paper is focused on introducing a hill-climbing algorithm as a way to solve the problem of generating typical testors -or non-reducible descriptorsfrom a training matrix. All the algorithms reported in the state-of-the-art have exponential complexity. However, there are problems for which there is no need to generate the whole set of typical testors, but it suffices to find only a subset o...

One of the basic problems of user on manual wheelchair is overcoming architectural barriers (kerbs, stairs etc.) on its way. Even though many research studies have been reported in different fields to increase the independence of wheelchair users, the question of overcoming obstacles by a wheelchair always remains as topic of discussion for many researchers. In this paper, the author has propos...