Multiple objective optimization of the fleet sizing problem for road freight transportation.

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Bibliographic Details
Title: Multiple objective optimization of the fleet sizing problem for road freight transportation.
Authors: Zak, Jacek, Redmer, Adam, Sawicki, Piotr
Source: Journal of Advanced Transportation. Oct2008, Vol. 42 Issue 4, p379-427. 49p.
Subjects: Mathematical models, Multiple criteria decision making, Mathematical programming, Queuing theory, Freight & freightage, Transportation
Abstract: A fleet sizing problem (FSP) in a road freight transportation company with heterogeneous fleet and its own technical back-up facilities is considered in the paper. The mathematical model of the decision problem is formulated in terms of multiple objective mathematical programming based on queuing theory. Technical and economical criteria as well as interests of different stakeholders are taken into account in the problem formulation. The solution procedure is composed of two steps. In the first one a sample of Pareto-optimal solutions is generated by an original program called MEGROS. In the second step this set is reviewed and evaluated, according to the Decision Maker's (DM's) model of preferences. The evaluation of solutions is carried out with an application of an interactive multiple criteria analysis method, called Light Beam Search (LBS). Finally, the DM selects the most desirable, compromise solution. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:A fleet sizing problem (FSP) in a road freight transportation company with heterogeneous fleet and its own technical back-up facilities is considered in the paper. The mathematical model of the decision problem is formulated in terms of multiple objective mathematical programming based on queuing theory. Technical and economical criteria as well as interests of different stakeholders are taken into account in the problem formulation. The solution procedure is composed of two steps. In the first one a sample of Pareto-optimal solutions is generated by an original program called MEGROS. In the second step this set is reviewed and evaluated, according to the Decision Maker's (DM's) model of preferences. The evaluation of solutions is carried out with an application of an interactive multiple criteria analysis method, called Light Beam Search (LBS). Finally, the DM selects the most desirable, compromise solution. [ABSTRACT FROM AUTHOR]
ISSN:01976729
DOI:10.1002/atr.5670420402