The multiple container loading cost minimization problem

2011 ◽  
Vol 214 (3) ◽  
pp. 501-511 ◽  
Author(s):  
Chan Hou Che ◽  
Weili Huang ◽  
Andrew Lim ◽  
Wenbin Zhu
2020 ◽  
Vol 15 (3) ◽  
pp. 162-168
Author(s):  
Dian Pratiwi Sahar ◽  
Mohammad Thezar Afifudin

Penelitian ini bertujuan untuk mengembangkan model matematika untuk masalah minimisasi biaya pemuatan multi-kontainer dengan enam variabel orientasi kargo. Masalah ini dirumuskan sebagai model pemrograman linier biner integer untuk meminimalkan biaya. Faktor-faktor yang dipertimbangkan dalam formulasi termasuk alokasi kargo, lokasi kargo, hubungan kargo, dan orientasi kargo. Sedangkan, biaya yang dipertimbangkan termasuk biaya muatan volume kontainer ke kargo dan biaya transportasi kargo ke kontainer. Validasi model dilakukan melalui percobaan numerik pada ukuran kecil kargo dan kontainer. Hasil penelitian menunjukkan bahwa model dengan konsep orientasi kargo yang dikembangkan dapat menyelesaikan masalah sesuai dengan parameter numerik yang diberikan. Abstract[Integer Linear Programming with Six Cargo Orientation Variables for Multi-Container Loading Cost Minimization Problem] This research aims to develop the mathematic model for multi-container loading cost minimization problems with six cargo orientation variables. The problem is formulated as a binary integer linear programming model to minimize costs. The factors considered in the formulation include cargo allocation, cargo location, cargo relations, and cargo orientation. Whereas, the costs considered include the container volume load cost to cargo and the cargo transport cost to the container. Model validation is performed through numerical experiments on the small size of cargo and containers. The results show that the model with developed cargo orientation concept can solve the problem according to the given numerical parameters.Keywords: integer programming; cargo orientation; container loading; cost minimization


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Bang Wang ◽  
Qiao Kong ◽  
Qiang Yang

The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.


2012 ◽  
Vol 26 (1-2) ◽  
pp. 249-267 ◽  
Author(s):  
Xiang Li ◽  
Chen-Fu Chien ◽  
Lixing Yang ◽  
Ziyou Gao

2019 ◽  
Vol 29 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Tatiana Gruzdeva ◽  
Rentsen Enkhbat ◽  
Natsagdorj Tungalag

This paper was motivated by a practical optimization problem that appeared in electricity market of Mongolia. We consider the total average cost minimization problem of power companies of the Ulaanbaatar city. By solving an identification problem, we developed a fractional model that quite adequately represents the real data. The obtained problem turned out to be a fractional minimization problem over a box constraint, and to solve it, we propose a method that employs the global search theory for d.c. minimization.


2013 ◽  
Vol 20 (5) ◽  
pp. 627-643 ◽  
Author(s):  
L. De Giovanni ◽  
G. Massi ◽  
F. Pezzella ◽  
M.E. Pfetsch ◽  
G. Rinaldi ◽  
...  

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