Memetic Algorithms with Local Search Chains in R: The Rmalschains Package
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چکیده
منابع مشابه
Memetic Algorithms for Continuous Optimisation Based on Local Search Chains
Memetic algorithms with continuous local search methods have arisen as effective tools to address the difficulty of obtaining reliable solutions of high precision for complex continuous optimisation problems. There exists a group of continuous local search algorithms that stand out as exceptional local search optimisers. However, on some occasions, they may become very expensive, because of the...
متن کاملPackage ‘ Rmalschains ’ August 29 , 2013
August 29, 2013 Maintainer Christoph Bergmeir License GPL-3 | file LICENSE Title Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R LinkingTo Rcpp Type Package LazyLoad yes Author Christoph Bergmeir, Daniel Molina, José M. Benítez Description This package implements an algorithm family for continuous optimization called memet...
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Nowadays, large scale optimisation problems arise as a very interesting field of research, because they appear in many real-world problems (bio-computing, data mining, etc.). Thus, scalability becomes an essential requirement for modern optimisation algorithms. In a previous work, we presented memetic algorithms based on local search chains. Local search chain concerns the idea that, at one sta...
متن کاملMemetic Algorithm for Intense Local Search Methods Using Local Search Chains
This contribution presents a new memetic algorithm for continuous optimization problems, which is specially designed for applying intense local search methods. These local search methods make use of explicit strategy parameters to guide the search, and adapt these parameters with the purpose of producing more effective solutions. They may achieve accurate results, at the cost of requiring high ...
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The 0-1 knapsack problem (KP) is widely studied in the last few decades. Despite of their simple structures, KP along with its extended versions belong to the class of NP-hard problems, and several optimization techniques have been developed to solve the problems. Some major examples are branch and bound methods and dynamic programming approaches [6], problemspecific heuristics [6], tabu search...
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ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2016
ISSN: 1548-7660
DOI: 10.18637/jss.v075.i04