The fleet size and mix location-routing problem with time windows: formulations and a heuristic algorithm
The fleet size and mix location-routing problem with time windows: formulations and a heuristic algorithm
This paper introduces the fleet size and mix location-routing problem with time windows (FSML- RPTW) which extends the location-routing problem by considering a heterogeneous fleet and time windows. The main objective is to minimize the sum of vehicle fixed cost, depot cost and routing cost. We present mixed integer programming formulations, a family of valid inequalities and we develop a powerful hybrid evolutionary search algorithm (HESA) to solve the problem. The HESA successfully combines several metaheuristics and offers a number of new advanced efficient procedures tailored to handle heterogeneous fleet dimensioning and location decisions. We evaluate the strengths of the proposed formulations with respect to their ability to find optimal solutions. We also investigate the performance of the HESA. Extensive computational experiments on new benchmark instances have shown that the HESA is highly effective on the FSMLRPTW.
terrestrial laser scanning (TLS), accuracy, error, georeferencing, registration, point clouds
33-51
Koc, C.
0580305f-af8c-49fa-b6a8-832f951c9e85
Bektas, T.
0db10084-e51c-41e5-a3c6-417e0d08dac9
Jabali, O.
7a91105c-3ff6-4a2c-bb86-0b5739af4faa
Laporte, G.
2cd560e2-79a4-4ee7-b883-ec02bc880328
1 January 2016
Koc, C.
0580305f-af8c-49fa-b6a8-832f951c9e85
Bektas, T.
0db10084-e51c-41e5-a3c6-417e0d08dac9
Jabali, O.
7a91105c-3ff6-4a2c-bb86-0b5739af4faa
Laporte, G.
2cd560e2-79a4-4ee7-b883-ec02bc880328
Koc, C., Bektas, T., Jabali, O. and Laporte, G.
(2016)
The fleet size and mix location-routing problem with time windows: formulations and a heuristic algorithm.
European Journal of Operational Research, 248 (1), .
(doi:10.1016/j.ejor.2015.06.082).
Abstract
This paper introduces the fleet size and mix location-routing problem with time windows (FSML- RPTW) which extends the location-routing problem by considering a heterogeneous fleet and time windows. The main objective is to minimize the sum of vehicle fixed cost, depot cost and routing cost. We present mixed integer programming formulations, a family of valid inequalities and we develop a powerful hybrid evolutionary search algorithm (HESA) to solve the problem. The HESA successfully combines several metaheuristics and offers a number of new advanced efficient procedures tailored to handle heterogeneous fleet dimensioning and location decisions. We evaluate the strengths of the proposed formulations with respect to their ability to find optimal solutions. We also investigate the performance of the HESA. Extensive computational experiments on new benchmark instances have shown that the HESA is highly effective on the FSMLRPTW.
Text
Paper3_EJORRevision.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 30 June 2015
e-pub ahead of print date: 17 July 2015
Published date: 1 January 2016
Keywords:
terrestrial laser scanning (TLS), accuracy, error, georeferencing, registration, point clouds
Organisations:
Centre of Excellence in Decision, Analytics & Risk Research
Identifiers
Local EPrints ID: 378590
URI: http://eprints.soton.ac.uk/id/eprint/378590
ISSN: 0377-2217
PURE UUID: 87ebcbcb-fe14-4cfb-a586-d9770424571d
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Date deposited: 08 Jul 2015 16:12
Last modified: 15 Mar 2024 05:19
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Contributors
Author:
C. Koc
Author:
T. Bektas
Author:
O. Jabali
Author:
G. Laporte
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