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http://repositorio.ufc.br/handle/riufc/71932
Type: | Artigo de Periódico |
Title: | Variable fixing heuristics for the capacitated multicommodity network flow problem with multiple transport lines, a heterogeneous fleet and time windows |
Authors: | Guimarães, Lucas Rebouças Sousa, Jorge Pinho de Prata, Bruno de Athayde |
Keywords: | Combinatorial optimization;Network design problems;Mixed integer linear programming;City logistics;Size reduction algorithms |
Issue Date: | 2022 |
Publisher: | Transportation Letters |
Citation: | GUIMARÃES, Lucas Rebouças; SOUSA, Jorge Pinho de; PRATA, Bruno de Athayde. Variable fixing heuristics for the capacitated multicommodity network flow problem with multiple transport lines, a heterogeneous fleet and time windows. Transportation Letters, [S. l.], v. 14, n. 2, p. 84-93, 2022. |
Abstract: | In this paper, we investigate a new variant of the multi-commodity network flow problem, taking into consideration multiple transport lines and time windows. This variant arises in a city logistics environment, more specifically in a long-haul passenger transport system that is also used to transport urban freight. We propose two mixed integer programming models for two objective functions: minimization of network operational costs and minimization of travel times. Since the problems under study are NP-hard, we propose three size reduction heuristics. In order to assess the performance of the proposed algorithms, we carried out computational experiments on a set of synthetic problem instances. We use the relative percentage deviation as performance criterion. For the cost objective function, a LP-and-Fix algorithm outperforms other methods in most tested instances, but for the travel time, a hybrid method (size reduction with LP-and- Fix algorithm) is, in general, better than other approaches. |
URI: | http://www.repositorio.ufc.br/handle/riufc/71932 |
ISSN: | 1942-7875 |
Access Rights: | Acesso Aberto |
Appears in Collections: | DEHA - Artigos publicados em revista científica |
Files in This Item:
File | Description | Size | Format | |
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2022_art_lrguimaraes1.pdf | 2,01 MB | Adobe PDF | View/Open |
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