Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach

被引：10

作者：

Haddouch, Khalid ^{[1
]}

Elmoutaoukil, Karim ^{[1
]}

Ettaouil, Mohamed ^{[2
]}

机构：

[1] Univ Mohammed First, Natl Sch Appl Sci Al Hoceima, Box 03, Al Hoceima, Morocco

[2] Univ Sidi Mohammed ben Abdellah, Fac Sci & Technol Fez, Modeling & Sci Comp Lab, Box 2202, Fes, Morocco

来源：

INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2016年 / 4卷 / 01期

关键词：

Weighted Constraint Satisfaction Problems; Quadratic; 0-1; Programming; Continuous Hopfield Network; Energy Function;

D O I：

10.9781/ijimai.2016.4111

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A wide variety of real world optimization problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs). In this paper, we model this problem in terms of in original 0-1 quadratic programming subject to leaner constraints. View it performance, we use the continuous Hopfield network to solve the obtained model basing on original energy function. To validate our model, we solve several instance of benchmarking WCSP. In this regard, our approach recognizes the optimal solution of the said instances.

引用

页码：56 / 60

页数：5

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