A recursive model for static empty container allocation

2011 ◽  
Vol 5 (4) ◽  
pp. 486-495
Author(s):  
Zijian Guo ◽  
Wenyuan Wang ◽  
Guolei Tang ◽  
Jun Huang
Keyword(s):  
Empty Container ◽  
Recursive Model

scholarly journals Simulation of empty container logistic management at depot

2017 ◽  
Author(s):  
San-Nah Sze ◽  
Siaw-Ying Doreen Sek ◽  
Kang-Leng Chiew ◽  
Wei-King Tiong
Keyword(s):  
Empty Container ◽  
Logistic Management

Determining optimal inland-empty-container depot locations under stochastic demand

2013 ◽  
Vol 42 (1) ◽  
pp. 50-60 ◽  
Author(s):  
Neha Mittal ◽  
Maria Boile ◽  
Alok Baveja ◽  
Sotiris Theofanis
Keyword(s):  
Stochastic Demand ◽  
Empty Container

Application of a mixed fuzzy decision making and optimization programming model to the empty container allocation

2010 ◽  
Vol 10 (4) ◽  
pp. 1071-1079 ◽  
Author(s):  
Chien-Chang Chou ◽  
Rong-Hua Gou ◽  
Chaur-Luh Tsai ◽  
Ming-Cheng Tsou ◽  
Chun-Pong Wong ◽  
...  
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Empty Container ◽  
Optimization Programming

scholarly journals An inland-depots-for-empty-containers-model for the hinterland

2017 ◽  
Vol 2 (2) ◽  
pp. 126-141 ◽  
Author(s):  
Stephanie Finke ◽  
Herbert Kotzab
Keyword(s):  
Linear Optimization ◽  
Point Of View ◽  
Mixed Integer ◽  
Total System ◽  
Empty Container ◽  
Content Type ◽  
Shipping Company ◽  
Linear Optimization Model ◽  
Mixed Integer Linear Optimization ◽  
Empty Containers

Purpose The purpose of this paper is to figure out in which way a hinterland-based inland depot model can help a shipping company in solving the empty container problem at a regional level. The repositioning of empty containers is a very expensive operation that does not generate profits. Consequently, it is very important to provide an efficient empty container management. Design/methodology/approach In this paper, the empty container problem is discussed at a regional repositioning level. For solving this problem, a mixed-integer linear optimization model is developed and validated by using the German hinterland as a case. Findings The findings show that the hinterland-based solution is able to reduce the total system costs by 40 per cent. In addition, total of truck kilometres could be reduced by more than 30 per cent too. Research limitations/implications This research is based on German data only. Originality/value This paper closes the gap in empty container repositioning research by looking at the hinterland dimension from a single shipping company point of view.

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