Publication date: Available online 9 June 2017
Source:Data in Brief
Author(s): Sadeque Hamdan, Ali Cheaitou
This data article provides detailed optimization input and output datasets and optimization code for the published research work titled "Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability" [1]. Researchers may use these datasets as a baseline for future comparison and extensive analysis of the green supplier selection and order allocation problem with all-unit quantity discount and varying number of suppliers. More particularly, the datasets presented in this article allow researchers to generate the exact optimization outputs obtained by the authors of [1] using the provided optimization code and then to use them for comparison with the outputs of other techniques or methodologies such as heuristic approaches. Moreover, this article includes the randomly generated optimization input data and the related outputs that are used as input data for the statistical analysis presented in [1] in which two different approaches for ranking potential suppliers are compared. This article also provides the time analysis data used in [1] to study the effect of the problem size on the computation time as well as an additional time analysis dataset. The input data for the time study are generated randomly, in which the problem size is changed, and then are used by the optimization problem to obtain the corresponding optimal outputs as well as the corresponding computation time.
http://ift.tt/2rMswdK
Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,00306932607174,alsfakia@gmail.com,
Ετικέτες
Σάββατο 10 Ιουνίου 2017
Datasets for supplier selection and order allocation with green criteria, all-unit quantity discounts and varying number of suppliers
Εγγραφή σε:
Σχόλια ανάρτησης (Atom)
-
Summary Insulinomas are rare neuroendocrine tumours that classically present with fasting hypoglycaemia. This case report discusses an un...
-
The online platform for Taylor & Francis Online content New for Canadian Journal of Remote Sen...
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου