We present a general picture of the parallel meta-heuristic search for optimization. We recall the main concepts and strategies in designing parallel metaheuristics, pointing to a number of contributions that instantiated them for neighborhoodand populationbased meta-heuristics, and identify trends and promising research directions. We focus on cooperation-based strategies, which display remark...

Discrete location theory is one of the most dynamic areas of operations research. We present the basic mathematical models used in this field, as well as their properties and relationship with pseudo-Boolean functions. We also investigate the theory of PLS-complete problems, average and worst case computational complexity of the local search algorithms, and approximate local search. Finally, we...

This paper presents a grid-based interaction model that is designed to encourage searchers to organize a complex search space by managing n×m sub spaces. A search interface was developed based on the proposed interaction model, and its performance was evaluated by a user study carried out in the context of the NTCIR-9 VisEx Task. This paper reports findings from the experiment and discusses fut...

Subgroup discovery (SD) is a descriptive data mining technique using supervised learning. In this article, we review the use of evolutionary algorithms (EAs) for SD. In particular, we will focus on the suitability and potential of the search performed by EAs in the development of SD algorithms. Future directions in the use of EAs for SD are also presented in order to show the advantages and ben...

This paper presents a coin recognition system based completely on the direction of the gradient vectors. To optimally align two coins we search for a rotation such that as most as possible corresponding gradient vectors point into the same direction. After discretizing the gradient directions this can be done quickly by the use of the Fast Fourier Transform. The classification is done by a simp...

In this work, we consider block-Jacobi methods with Newton steps in each subspace search and prove their local quadratic convergence to a local minimum with non-degenerate Hessian under some orthogonality assumptions on the search directions. Moreover, such a method is exemplified for non-unitary joint matrix diagonalization, where we present a block-Jacobi-type method on the oblique manifold w...

Multi-Point Constructive Search maintains a small set of “elite solutions” that are used to heuristically guide constructive search through periodically restarting search from an elite solution. Empirical results indicate that for job shop scheduling optimization problems, multi-point constructive search leads to significantly better solutions for equivalent search effort when compared to chron...

in this research work, the impact of user’s behavior on search engine results is discussed. it aims to improvement of search results which leads to the higher satisfaction of users. in other words, we are trying to present a personalized search engine for each user, based on his/her activity and search history. we base our hypothesis that the search history of each user in a specific time frame...

this paper considers the search problem, introduced by srivastava cite{sr}. this is a model discrimination problem. in the context of search linear models, discrimination ability of search designs has been studied by several researchers. some criteria have been developed to measure this capability, however, they are restricted in a sense of being able to work for searching only one possible non...

This paper describes a fall-back procedure for use with the Gauss-Newton method for nonlinear least-squares problems. While the basic Gauss-Newton algorithm is often successful, it is well-known that it can sometimes generate poor search directions and exhibit slow convergence. For dealing with such situations we suggest a new two-dimensional search strategy. Numerical experiments indicate that...