The Profitable Close-Enough Arc Routing Problem
In this article, the authors deal with the Profitable Close-Enough Arc Routing Problem (PCEARP), which is an extension of the Close-Enough ARP (CEARP). The CEARP models the situation in which customers are not necessarily nodes of a network and the associated serviced can be performed from any traversed edge that is close enough to the customer. It consists of finding a minimum cost tour that services all the customers. In the PCEARP, a profit is associated with each customer and it is collected (only once) when the customer is serviced. The goal is to find a tour maximizing the difference between the total profit collected and the travel distance. A formulation for this new problem and some valid inequalities are presented, and a polyhedral study of its feasible solutions is conducted. The authors propose a heuristic and a branch-and-cut procedure for solving the PCEARP, and their performance has been tested on several sets of instances with different characteristics.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/1793974
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Supplemental Notes:
- © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Bianchessi, Nicola
- Corberán, Ángel
- Plana, Isaac
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0000-0002-0516-4608
- Reula, Miguel
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0000-0002-6978-6780
- Sanchis, José M
- Publication Date: 2022-4
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 105653
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Serial:
- Computers & Operations Research
- Volume: 140
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0305-0548
- Serial URL: https://www.sciencedirect.com/journal/computers-and-operations-research
Subject/Index Terms
- TRT Terms: Branch and bound algorithms; Heuristic methods; Profitability; Routing
- Identifier Terms: Vehicle Routing Problem
- Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01850137
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 27 2022 5:16PM