Multiobjective Vehicle Routing Problems With Simultaneous Delivery and Pickup and Time Windows: Formulation, Instances, and Algorithms
Author(s) -
Jiahai Wang,
Ying Zhou,
Yong Wang,
Jun Zhang,
C. L. Philip Chen,
Zibin Zheng
Publication year - 2016
Publication title -
ieee transactions on cybernetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.109
H-Index - 124
eISSN - 2168-2275
pISSN - 2168-2267
DOI - 10.1109/tcyb.2015.2409837
Subject(s) - signal processing and analysis , communication, networking and broadcast technologies , robotics and control systems , general topics for engineers , components, circuits, devices and systems , computing and processing , power, energy and industry applications
This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry. VRPSDPTW is an important logistics problem in closed-loop supply chain network optimization. VRPSDPTW exhibits multiobjective properties in real-world applications. In this paper, a general multiobjective VRPSDPTW (MO-VRPSDPTW) with five objectives is first defined, and then a set of MO-VRPSDPTW instances based on data from the real-world are introduced. These instances represent more realistic multiobjective nature and more challenging MO-VRPSDPTW cases. Finally, two algorithms, multiobjective local search (MOLS) and multiobjective memetic algorithm (MOMA), are designed, implemented and compared for solving MO-VRPSDPTW. The simulation results on the proposed real-world instances and traditional instances show that MOLS outperforms MOMA in most of instances. However, the superiority of MOLS over MOMA in real-world instances is not so obvious as in traditional instances.
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