scholarly journals A Model of Systems Dynamics for Physical Flow Analysis in a Distribution Supply Chain

2021 ◽  
Vol 22 (1) ◽  
pp. 98-108
Author(s):  
Kahina Hamoudi ◽  
Ahmed Bellaouar ◽  
Romain Petiot

AbstractThis article proposes a model of systems dynamics for the analysis and study of physical flows in a distribution logistics chain. The proposed model is a decision support tool that allows testing several scenarios in order to study the behavior of physical flows within a supply chain depending on the inventory and transport costs and taking into consideration the environmental issues through the integration of a CO2 tax in transport costs. The developed model can be used to analyze various scenarios and perform various “what-if” analyzes, as well as to answer questions about the long-term operation of distribution chains. The results show that logistic decisions and strategies taken at the supply chain level influence inventory and transport costs. They show also that the model is a well decision-support tool for calculating and analyzing transport and inventory costs. We first expose the methodology and the literature review. Next, we present in detail the structure of the model consisting of the causal loops diagram and stock and flow diagram. Finally, we discuss the results of the model.

Author(s):  
Eirill Bø

Transport is an important function in the supply chain. This chapter focuses on how to buy a transport service, how to form a transport contract, and how a transparent relationship will influence the risk and the relationship between transport provider and buyer. By developing a decision support tool (DST-model) and calculating the cost and the time parameters, the right price and the cost drivers will appear. The cases described in this chapter are a large Norwegian wholesaler for food, distribution to the retailer, and two Norwegian municipalities collecting household waste. In these cases, the buyer and the provider are acting blind in setting the transport price. This means that there is a huge risk for either a bankruptcy by the transport provider or an overpriced transport for the buyer.


2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.


SIMULATION ◽  
2003 ◽  
Vol 79 (3) ◽  
pp. 126-138 ◽  
Author(s):  
Peter Lendermann ◽  
Nirupam Julka ◽  
Boon Ping Gan ◽  
Dan Chen ◽  
Leon F. McGinnis ◽  
...  

2021 ◽  
Vol 125 ◽  
pp. 103391
Author(s):  
Sonia Cisneros-Cabrera ◽  
Grigory Pishchulov ◽  
Pedro Sampaio ◽  
Nikolay Mehandjiev ◽  
Zixu Liu ◽  
...  

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