An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

Joint Authors

Rao, Weizhen
Liu, Feng
Wang, Shengbin

Source

Applied Computational Intelligence and Soft Computing

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-03-07

Country of Publication

Egypt

No. of Pages

16

Main Subjects

Information Technology and Computer Science

Abstract EN

The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles.

Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention.

The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult.

We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient.

Complexity analysis of FCVRP is presented through analogy with the capacitated VRP.

To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS).

TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP.

Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested.

Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

American Psychological Association (APA)

Rao, Weizhen& Liu, Feng& Wang, Shengbin. 2016. An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem. Applied Computational Intelligence and Soft Computing،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1094901

Modern Language Association (MLA)

Rao, Weizhen…[et al.]. An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem. Applied Computational Intelligence and Soft Computing No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1094901

American Medical Association (AMA)

Rao, Weizhen& Liu, Feng& Wang, Shengbin. An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem. Applied Computational Intelligence and Soft Computing. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1094901

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1094901