Stochastic Local Search Algorithms
نویسندگان
چکیده
The Genomic Median Problem is an optimization problem inspired by a biological issue: it aims at finding the genome organization of the common ancestor to multiple living species. It is formulated as the search for a genome that minimizes some distance measure among given genomes. Several attempts have been made at solving the problem. These range from simple heuristic methods to a stochastic local search (SLS) algorithm that is inspired by a well-known local search algorithm for the satisfiability problem in propositionnal logic, called WalkSAT. The objective of this study is to implement improved algorithmic techniques, particularly ones based on tabu search, in the quest for better quality solutions for large instances of the problem. We have engineered a new high-performing SLS algorithm, extensively tested the developed algorithm and found a new best solution for a real-world case.
منابع مشابه
Training Radial Basis Function Neural Network using Stochastic Fractal Search Algorithm to Classify Sonar Dataset
Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...
متن کاملDevelopment of an Efficient Hybrid Method for Motif Discovery in DNA Sequences
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...
متن کاملWinner Determination in Combinatorial Auctions using Hybrid Ant Colony Optimization and Multi-Neighborhood Local Search
A combinatorial auction is an auction where the bidders have the choice to bid on bundles of items. The WDP in combinatorial auctions is the problem of finding winning bids that maximize the auctioneer’s revenue under the constraint that each item can be allocated to at most one bidder. The WDP is known as an NP-hard problem with practical applications like electronic commerce, production manag...
متن کاملA Hybrid Algorithm using Firefly, Genetic, and Local Search Algorithms
In this paper, a hybrid multi-objective algorithm consisting of features of genetic and firefly algorithms is presented. The algorithm starts with a set of fireflies (particles) that are randomly distributed in the solution space; these particles converge to the optimal solution of the problem during the evolutionary stages. Then, a local search plan is presented and implemented for searching s...
متن کاملEngineering Stochastic Local Search Algorithms: A Case Study in Estimation-Based Local Search for the Probabilistic Travelling Salesman Problem
In this article, we describe the steps that have been followed in the development of a high performing stochastic local search algorithm for the probabilistic travelling salesman problem, a paradigmatic combinatorial stochastic optimization problem. In fact, we have followed a bottom-up algorithm engineering process that starts from basic algorithms (here, iterative improvement) and adds comple...
متن کاملOn the Run-time Behaviour of Stochastic Local Search Algorithms for SAT
Stochastic local search (SLS) algorithms for the propositional satisfiability problem (SAT) have been successfully applied to solve suitably encoded search problems from various domains. One drawback of these algorithms is that they are usually incomplete. We refine the notion of incompleteness for stochastic decision algorithms by introducing the notion of “probabilistic asymptotic completenes...
متن کامل