Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9750
Title: Transportation Network Optimization
Authors: Kalganova, T
Ogunbanwo, A
Williamson, A
Veluscek, M
Izsak, R
Broomhead, P
Keywords: Transportation;Longevity;Optimization objectives
Issue Date: 2014
Publisher: IGI Global
Citation: Encyclopaedia of Business Analytics and Optimization, pp. 2570 - 2583, 2014
Abstract: The longevity of transportation networks dates back to the age of ancient civilization, since that time the main objective has in essence remained the same: to facilitate the transportation of goods from one location to another using the most cost effective mean available. To rephrase that in modern vernacular, the management and optimization of transportation networks in meeting business objectives. While the forces driving the interpretation of most cost effective means available have changed overtime with the introduction of new technologies, global trade links and governmental policies; the general expectation of a transportation network has remained constant. These driving forces have impacted on the perception of optimality; cost is not necessarily the sole objective these days. Optimization objectives such as energy costs and their variability, time, environmental impact but to name a few have growing in importance of late. Many of the existing approaches to supply chain management take a multi-objective optimization approach, combining several (possibly competing) objectives and optimize the network. As such there is a growing trend to perform balanced optimization across a number of objectives. Transportation networks are rapidly expanding due to the globalization of business and supply chains; as such the size and complexity of transportation networks has increased considerably in the last decade. Transportation network optimization is known to be a difficult and complex problem to solve, a deterministic solution is often not applicable or indeed available for such problems and the problems themselves are therefore categorized as NP-hard problems. In response to the failure of deterministic algorithms to solve NP-hard problems, other optimization techniques have been developed and applied. The purpose of the paper is to review the current state of art in transportation network optimization. The paper is organized in five sections. In the Background section, we introduce the transportation problem, consider its theoretical aspects and implications, and perform a detailed analysis of the main contributions made in the field. In the Main Focus section, we present a critical analysis of the algorithms used, the objectives optimized and the complexity of the networks analyzed in the literature, and discuss the main problems that as yet remain to be addressed. In the Solutions and Recommendations section, we propose ideas, and possible solutions to these outstanding problems. Finally, in the Future Research Directions section, we discuss future and emerging trends.
URI: http://www.igi-global.com/book/encyclopedia-business-analytics-optimization/90651
http://bura.brunel.ac.uk/handle/2438/9750
DOI: http://dx.doi.org/10.4018/978-1-4666-5202-6
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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