Transportation mode selection in inventory models: A literature review

2019 ◽  
Vol 279 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Erna Engebrethsen ◽  
Stéphane Dauzère-Pérès
2015 ◽  
Vol 35 (1) ◽  
pp. 149-159 ◽  
Author(s):  
D. Battini ◽  
M. Gamberi ◽  
A. Persona ◽  
F. Sgarbossa

Purpose – The paper aims to focus on in-house part logistics design and management for assembly systems in which supermarket storage is adopted and coupled with an automated transportation system. In this context, this work aims to assess the transportation mode selection problem to speed up the preliminary design phase. Design/methodology/approach – The paper is divided into two main parts. The first one provides and discusses a new conceptual framework derived from the authors’ experience in the field and from previous published works. The framework aims to support managers in problem comprehension by setting three problem sub-phases, key input parameters and qualitative guidelines without losing sight of the big picture. The second part focuses on the transportation mode selection sub-phase by assessing an analytical study followed by a multi-scenario analysis. Findings – The final outcome of this work is a decision support matrix capable of setting technical guidelines that are helpful to managers and practitioners to speed up the transportation mode selection problem in the preliminary phases. Originality/value – This work is beneficial for supporting managers in understanding the main decisional steps involved in the design of a part-feeding system with a supermarket by discussing the three problem sub-phases and key input parameters and providing both qualitative and quantitative guidelines. Moreover, this study explores the transportation mode selection problem, which is not yet largely explored in the published literature.


Author(s):  
Hong Zhang ◽  
Kuan Yang

A well-designed supply chain network should not only meet the efficient cost but also realize the sustainable effect on environment. The purpose of this article is to develop a multi-objective model to capture the trade-off between total cost and environmental performance in the green dual-channel supply chain network. Moreover, the transportation mode has been considered as a decision variable. With regard to the complexity of such network, a new swarm intelligence algorithm known as a multi-objective particle swarm optimization (MOPSO) algorithm has been employed to tackle this problem. The effectiveness of the present model and approach is evaluated by a numerical experiment, and the results show that the added environmental performance is actually proportional with the increased cost. Additionally, the comparison between different mode decisions shows that a better trade-off between two objectives will be obtained when considering the transportation mode selection.


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