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This work does not use the classical methods (simplex method, Branch and Bound techniques) which were normally used for solving Linear programming models. The proposed algorithm was considered for implementation with Artificial Neural Network (ANN) using MatLab tool box. It was found that implementation of the neural network will provide comprehensive results when applied with any linear programming models. Besides Artificial Neural Networks are artificial intelligence methods for modeling complex target functions, and are considered to be among the most effective learning methods currently known. Implementation in solving linear programming models became very interesting, as ANNs became appropriate solution where a huge data (number of variables and constraints) is considered. In this work, general model of ANN specified for solving the problem of linear programming will be shown and discussed.The results show a great improvement in prediction of results with a minimum percentage error.
In this work, the problem of job-machine assignment was formulated as a linear programming (LP) models and then solved by the simplex method. Three case studies were involved in this study to cover all kinds of problems may be faced. To verify the results of the LP models, these problems also solved using transportation algorithm and has been found that the LP model is more efficient for solving the assignment problems.
تهتم الدراسة الحالية ببناء نماذج رياضية خطية لحل مشكلات تخصيص الاعمال على المكائن. تم حل النماذج المقترحة باستعمال طريقة التبسيط simplex method. تم دراسة ثلاث حالات لغرض تغطية جميع حالات عملية تخصيص الاعمال على المكائن. لغرض التاكد من صحة النتائج و دقةها تم حل نفس النماذج باستعمال الطرائق التقليدية ولوحظ ان الحل باستعمال النماذج الخطية اكثر كفاءة" في حل مشكلات التخصيص.
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