A firefly algorithm for the heterogeneous fixed fleet vehicle routing problem

被引：3

作者：

Matthopoulos P.-P. ^{[1
]}

Sofianopoulou S. ^{[1
,2
]}

机构：

[1] Department of Industrial Management and Technology, University of Piraeus, 80 Karaoli and Dimitriou St., Piraeus

[2] Business School, University of Sunderland, St. Peter's Campus, Sunderland

来源：

International Journal of Industrial and Systems Engineering | 2019年 / 33卷 / 02期

关键词：

Combinatorial optimisation; Firefly algorithm; Nature inspired metaheuristic algorithms; Vehicle routing problem; VRP;

D O I：

10.1504/IJISE.2019.102471

中图分类号：

学科分类号：

摘要：

Vehicle routing is a key success factor in logistics problems. A variation of vehicle routing problem (VRP), the heterogeneous fixed fleet VRP in which the vehicles available for distribution activities are characterised by different capacities and costs, is tackled. A hybrid firefly algorithm for optimising the routing of heterogeneous fixed fleet of vehicles in logistics distribution systems is presented. The principles and key steps of the proposed firefly algorithm are introduced in detail. Experimental results from solving the heterogeneous fixed fleet vehicle routing problem when tested on benchmark datasets are demonstrated. Moreover, the algorithm is compared with other algorithms solving similar problems in order to prove the effectiveness of the proposed hybrid firefly algorithm. Copyright © 2019 Inderscience Enterprises Ltd.

引用

页码：204 / 224

页数：20

共 44 条

[11]

Ganesh K., Narendran T.T., CLOVES: A cluster-and-search heuristic to solve the vehicle routing problem with delivery and pick-up, European Journal of Operational Research, 178, 3, pp. 699-717, (2007)

[12]

Imanirad R., Yang X.S., Yeomans J.S., A biologically - Inspired metaheuristic procedure for modeling-to-generate-alternatives, International Journal of Engineering Research and Applications, 3, 2, pp. 1677-1686, (2013)

[13]

Jati G., Suyanto, Evolutionary discrete firefly algorithm for travelling salesman problem, Adaptive and Intelligent Systems, Lecture Notes in Computer Science, pp. 393-403, (2011)

[14]

Jati G., Manurung R., Suyanto, Discrete firefly algorithm for traveling salesman problem: A new movement scheme, Swarm Intelligence and Bio-inspired Computation Theory and Applications, pp. 295-312, (2013)

[15]

Javad M.O.M., Karimi B., A simulated annealing algorithm for solving multi-depot location routing problem with backhaul, International Journal of Industrial and Systems Engineering, 25, 4, pp. 460-477, (2017)

[16]

Juan A.A., Faulin J., Ruiz R., Barrios B., Caballe S., The SR-GCWS hybrid algorithm for solving the capacitated vehicle routing problem, Applied Soft Computing, 10, 1, pp. 215-224, (2010)

[17]

Khadwilad A., Chansombat S., Thepphakorn T., Thapatsuwan P., Chainate W., Pongcharoen P., Application of firefly algorithm and its parameter setting for job shop scheduling, The First Symposium on Hands-on Research and Development, pp. 1-10, (2011)

[18]

Koc C., Bektas T., Jabali O., Laporte G., A hybrid evolutionary algorithm for heterogeneous fleet vehicle routing problems with time windows, Computers & Operations Research, 64, pp. 11-27, (2015)

[19]

Koc C., Bektas T., Jabali O., Laporte G., Thirty years of heterogeneous vehicle routing, European Journal of Operational Research, 249, 1, pp. 1-21, (2015)

[20]

Kromer P., Abraham A., Snasel V., Berhan E., Kitaw D., On the differential evolution for vehicle routing problem, IEEE (SoCPaR 2013): Fifth International Conference of Soft Computing and Pattern Recognition, (2013)

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