This work presents a hybrid method for motif discovery in DNA sequences. The proposed method called SPSO-Lk, borrows the concept of Chebyshev polynomials and uses the stochastic local search to improve the performance of the basic PSO algorithm as a motif finder. The Chebyshev polynomial concept encourages us to use a linear combination of previously discovered velocities beyond that proposed b...

In this article, by Partitioning of designing space, optimization speed is tried to be increased by GA. To this end, designing space search is done in two steps which are global search and local search. To achieve this goal, according to meshing in FEM, firstly, the list of sections is divided to specific subsets. Then, intermediate member of each subset, as representative of subset, is defined...

In this paper, we study the complexity of computing locally optimal solutions for weighted versions of standard set problems such as SETCOVER, SETPACKING, and many more. For our investigation, we use the framework of PLS, as defined in Johnson et al., [13]. We show that for most of these problems, computing a locally optimal solution is already PLS-complete for a simple natural neighborhood of ...

A variety of metaheuristics have been developed to solve the permutation flow shop problem minimizing total flow time. Iterated local search (ILS) is a simple but powerful metaheuristic used to solve this problem. Fundamentally, ILS is a procedure that needs to be restarted from another solution when it is trapped in a local optimum. A new solution is often generated by only slightly perturbing...

In this report, we examine the potential use of Guided Local Search (GLS) for function optimization. In order to apply GLS, the function to be minimized is augmented with a set of penalty terms that enable local search to escape from local minima. The function F6 is used to demonstrate the proposed technique.

In the paper we investigate stochastic local search by Markov chain analysis in a high and a low dimensional discrete space. In the n-dimensional space Bn a function called Jump is considered. The analysis shows that an algorithm using a large neighborhood and never accepting worse points performs much better than any local search algorithm accepting worse points with a certain probability. We ...

This paper presents a simple iterated local search metaheuristic incorporating a k-opt local search (KLS), called Iterated KLS (IKLS for short), for solving the maximum clique problem (MCP). IKLS consists of three components: LocalSearch at which KLS is used, a Kick called LEC-Kick that escapes from local optima, and Restart that occasionally diversifies the search by moving to other points in ...

This papers aims at providing a combined strategy for solving systems of equalities and inequalities. The combined strategy uses two types of steps: a global search step and a local search step. The global step relies on a tabu search heuristic and the local step uses a deterministic search known as Hooke and Jeeves. The choice of step, at each iteration, is based on the level of reduction of t...

The genomic median problem aims at finding the organization of the chromosome of a common ancestor to multiple living species. The problem is often formulated as searching for a genome that minimizes some distance measure among given genomes. In our previous research we have proposed a new stochastic local search algorithm for this problem that combined elements of tabu search, iterated local s...