Applying dynamic multiple-objective optimization in inter-enterprise collaboration to improve the efficiency of energy wood transportation and storage

In Finland, VR Group (the state-owned railway company) provides third-party logistics services (3PLs) for industrial customers. Their current static, single-objective optimization model does not support inter-enterprise collaboration to achieve optimal railway logistics. In this study, I introduce a...

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Bibliographic Details
Published in:Scandinavian journal of forest research Vol. 30; no. 4; pp. 346 - 356
Main Author: Palander, Teijo
Format: Journal Article
Language:English
Published: Oslo Taylor & Francis 19.05.2015
Taylor & Francis LLC
Subjects:
3PL
Collaboration
consumers (people)
cost-efficiency
decision making
Efficiency
Finland
forest industries
imports
Linear programming
Logistics
Optimization
public ownership
rail transportation
railway traffic
research support
Russian tariffs
Storage
supply chain
traffic
Transportation
wagons
Wood
wood imports
Finland
ISSN:0282-7581, 1651-1891, 1651-1891
Online Access:Get full text
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Summary:In Finland, VR Group (the state-owned railway company) provides third-party logistics services (3PLs) for industrial customers. Their current static, single-objective optimization model does not support inter-enterprise collaboration to achieve optimal railway logistics. In this study, I introduce a collaborative decision-support method that can be applied to manage railway traffic under a scenario of increasing imports of Russian wood. Based on the data obtained to support this research, I describe railway traffic strategy scenarios in terms of 3PLs to account for the changed energy wood transportation and storage needs related to imported Russian wood. In the scenarios, the railway wagon rotation was adjusted to reach a globally optimal strategy that achieves efficient wood procurement logistics for the Finnish forest industry. These decisions were based on a comprehensive logistics analysis of the integrated wood demand and a supply chain model for southeastern Finland in the context of collaborative decision-making among members of the logistics chain. The model, which is based on dynamic multiple-objective linear programming, supports inter-enterprise collaboration because the adaptation of Russian wood imports to the regional railway transportation environment will require continuous, integrated optimization of the flows of wood and railway wagons.
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ISSN:0282-7581
1651-1891
1651-1891
DOI:10.1080/02827581.2014.1001780