A Multilevel Genetic Algorithm for the Maximum Satisfaction Problem

Genetic algorithms (GA) which belongs to the class of evolutionary algorithms are regarded as highly successful algorithms when applied to a broad range of discrete as well continuous optimization problems. This chapter introduces a hybrid approach combining genetic algorithm with the multilevel par...

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Main Author: Bouhmala, Noureddine (Author)
Format: Ebooks
Published: IntechOpen, 2018-06-27.
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100 1 0 |a Bouhmala, Noureddine  |e author 
245 0 0 |a A Multilevel Genetic Algorithm for the Maximum Satisfaction Problem 
260 |b IntechOpen,   |c 2018-06-27. 
500 |a https://mts.intechopen.com/articles/show/title/a-multilevel-genetic-algorithm-for-the-maximum-satisfaction-problem 
520 |a Genetic algorithms (GA) which belongs to the class of evolutionary algorithms are regarded as highly successful algorithms when applied to a broad range of discrete as well continuous optimization problems. This chapter introduces a hybrid approach combining genetic algorithm with the multilevel paradigm for solving the maximum constraint satisfaction problem (Max-CSP). The multilevel paradigm refers to the process of dividing large and complex problems into smaller ones, which are hopefully much easier to solve, and then work backward toward the solution of the original problem, using the solution reached from a child level as a starting solution for the parent level. The promising performances achieved by the proposed approach are demonstrated by comparisons made to solve conventional random benchmark problems. 
540 |a https://creativecommons.org/licenses/by/3.0/ 
546 |a en 
690 |a Artificial Intelligence - Emerging Trends and Applications 
655 7 |a Chapter, Part Of Book  |2 local 
786 0 |n https://www.intechopen.com/books/6646 
787 0 |n ISBN:978-1-78923-364-3 
856 \ \ |u https://mts.intechopen.com/articles/show/title/a-multilevel-genetic-algorithm-for-the-maximum-satisfaction-problem  |z Get Online