This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics...
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This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics of intermodal transport using multi-modes, and presents a Weighted Constrained Shortest Path Problem (WCSPP) model. This study draws Pareto optimal solutions that can simultaneously meet two objective functions by applying the label setting algorithm, a type of Dynamic Programming algorithms, after setting the feasible area. To improve the algorithm performance, pruning rules have also been presented. The algorithm is applied to real transport paths from Busan to Rotterdam, as well as to large-scale cases. This study quantitatively measures the savings in both transport cost and time by comparing single transport modes with intermodal transport paths. Last, this study applies a mathematical model and MADM model to the multiple Pareto optimal solutions to estimate the solutions.
We consider the biobjective shortest path (BSP) problem as the natural extension of the single-objective shortest path problem. BSP problems arise in various applications where networks usually consist of large number...
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We consider the biobjective shortest path (BSP) problem as the natural extension of the single-objective shortest path problem. BSP problems arise in various applications where networks usually consist of large numbers of nodes and arcs. Since obtaining the set of efficient solutions to a BSP problem is more difficult (i.e. NP-hard and intractable) than solving the corresponding single-objective problem there is a need for fast solution techniques. Our aim is to compare different strategies for solving the BSP problem. We consider a standard label correcting and labelsetting method, a purely enumerative near shortest path approach, and the two phase method, investigating different approaches to solving problems arising in phases 1 and 2. In particular, we investigate the two phase method with ranking in phase 2. In order to compare the different approaches. we investigate their performance oil three different types of networks. We employ grid networks and random networks, as is generally done in the literature. Furthermore, road networks are utilized to compare performance on networks with a structure that is more likely to actually arise in applications. (C) 2008 Elsevier Ltd. All rights reserved.
This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics...
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ISBN:
(纸本)9783540733225
This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics of intermodal transport using two or more modes, and presents a Weighted Constrained Shortest Path Problem (WCSPP) model. This study draws a Pareto optimal solution that can simultaneously meet two objective functions by applying the label setting algorithm, one of the Dynamic Programming algorithms, after setting feasible area using the objective function values drawn in the model. To improve the algorithm performance, pruning rules have also been presented. The algorithm is applied to real transport paths from Busan to Rotterdam. This study quantitatively measures the savings effect of transport cost and time by comparing single transport modes with existin intermodal transport paths. Lastly, this study applies the multiple Pareto optimal solutions drawn, to a mathematical model and MADM model, and compares the two evaluation methods as a means to evaluate the solutions.
In this paper we generalize the classical shortest path problem in two ways. We consider two objective functions and time-dependent data. The resulting problem, called the time-dependent bicriteria shortest path probl...
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In this paper we generalize the classical shortest path problem in two ways. We consider two objective functions and time-dependent data. The resulting problem, called the time-dependent bicriteria shortest path problem (TdBiSP), has several interesting practical applications, but has not gained much attention in the literature. After reviewing relevant literature we develop a new algorithm for the TdBiSP with non-negative data. Numerical tests show the superiority of our algorithm compared with an existing algorithm in the literature. Furthermore, we discuss algorithms for the TdBiSP with negative travel times and costs. (c) 2006 Elsevier B.V. All rights reserved.
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