In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Experiments show that this approach achieves the best solution quality when compared with the GPS [1] algorithm, Tabu ...

We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.

1 Introduction In contrast to stationary problems where the problem parameters are static, dynamic optimisation problems (DOPs) present a challenging research area to the community [1]. This is mainly because, changes can occur any time during the optimisation course. Hence, when such a change happens (for example a change in the fitness landscape), the previous local optimal solution is no lon...

A class of problems referred to as Order Independent Minimum Grouping Problems is examined and an intuitive hill-climbing method for solving such problems is proposed. Example applications of this generic method are made to two well-known problems belonging to this class: graph colouring and bin packing. Using a wide variety of different problem instance-types, these algorithms are compared to ...

Program Transformations are generally written in order to generate better programs. In transformations, we apply a number of simple transformation axioms to parts of a program source code to obtain a functionally equivalent program. The application of these axioms is treated as a search problem and we apply a meta–heuristic search algorithm such as hill climbing to guide the direction of the se...

The Traveling Tournament Problem (TTP) schedules a double roundrobin tournament to minimize the total distance traveled by competing teams. It involves issues of feasibility and optimality and is challenging for both constraint programming and integer programming. This paper considers the TTP proposed in [4],[[12]. We divide the search space into two subspaces. Simulated Annealing (SA) is used ...

This paper describes a stochastic hill climbing algorithm named SHCLVND to optimize arbitrary vectorial < n ! < functions. It needs less parameters. It uses normal (Gaussian) distributions to represent probabilities which are used for generating more and more better argument vectors. The-parameters of the normal distributions are changed by a kind of Hebbian learning. Kvasnicka et al. KPP95] us...

Robotic assembly line balancing (RALB) is specific for robotic assembly, where different robots require different assembly times to perform the same task because of their specialization. The problem includes optimal assignment of robots to line stations and balanced distribution of work between different stations. It aims at maximizing the production rate of the line. This problem is solved by ...

In this paper we review some previously published experimental results in which a simple hillclimbing algorithm-Random Mutation Hill-Climbing (RMHC)-significantly outperforms a genetic algorithm on a simple "Royal Road" function. vVe present an analysis of RMHC followed by an analysis of an "idealized" genetic algorithm (IGA) that is in turn significantly faster than RMHC. We isolate the featur...

This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable actions, called action modules, to produce a plan for a given task. The search is performed with a hierarchical selection process that uses task and configuration filters to reduce the action module inventory to a reas...