Improved Cross Entropy Algorithm for the Optimum of Charge Planning Problem

المؤلفون المشاركون

Yang, Fan
Li, Qiqiang

المصدر

Abstract and Applied Analysis

العدد

المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-5، 5ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2014-07-01

دولة النشر

مصر

عدد الصفحات

5

التخصصات الرئيسية

الرياضيات

الملخص EN

To solve the charge planning problem involving charges and the orders in each charge, a traveling salesman problem based charge planning model and the improved cross entropy algorithm are proposed.

Firstly, the charge planning problem with unknown charge number is modeled as a traveling salesman problem.

The objective of the model is to minimize the dissimilarity costs between each order and its charge center order, the open order costs, and the unselected order costs.

Secondly, the improved cross entropy algorithm is proposed with the improved initial state transition probability matrix which is constructed according to the differences of steel grades and order widths between orders.

Finally, an actual numerical example shows the effectiveness of the model and the algorithm.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Yang, Fan& Li, Qiqiang. 2014. Improved Cross Entropy Algorithm for the Optimum of Charge Planning Problem. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-1014924

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Yang, Fan& Li, Qiqiang. Improved Cross Entropy Algorithm for the Optimum of Charge Planning Problem. Abstract and Applied Analysis No. 2014 (2014), pp.1-5.
https://search.emarefa.net/detail/BIM-1014924

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Yang, Fan& Li, Qiqiang. Improved Cross Entropy Algorithm for the Optimum of Charge Planning Problem. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-1014924

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1014924