Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows
Joint Authors
Leng, Longlong
Zhao, Yanwei
Zhang, Jingling
Wang, Zheng
Wang, Hongwei
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-31
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
In this paper, we consider a variant of the location-routing problem (LRP), namely, the regional low-carbon LRP with reality constraint conditions (RLCLRPRCC), which is characterized by clients and depots that located in nested zones with different speed limits.
The RLCLRPRCC aims at reducing the logistics total cost and carbon emission and improving clients satisfactory by replacing the travel distance/time with fuel consumption and carbon emission costs under considering heterogeneous fleet, simultaneous pickup and delivery, and hard time windows.
Aiming at this project, a novel approach is proposed: hyperheuristic (HH), which manipulates the space, consisted of a fixed pool of simple operators such as “shift” and “swap” for directly modifying the space of solutions.
In proposed framework of HH, a kind of shared mechanism-based self-adaptive selection strategy and self-adaptive acceptance criterion are developed to improve its performance, accelerate convergence, and improve algorithm accuracy.
The results show that the proposed HH effectively solves LRP/LRPSPD/RLCLRPRCC within reasonable computing time and the proposed mathematical model can reduce 2.6% logistics total cost, 27.6% carbon emission/fuel consumption, and 13.6% travel distance.
Additionally, several managerial insights are presented for logistics enterprises to plan and design the distribution network by extensively analyzing the effects of various problem parameters such as depot cost and location, clients’ distribution, heterogeneous vehicles, and time windows allowance, on the key performance indicators, including fuel consumption, carbon emissions, operational costs, travel distance, and time.
American Psychological Association (APA)
Leng, Longlong& Zhao, Yanwei& Wang, Zheng& Wang, Hongwei& Zhang, Jingling. 2018. Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1209514
Modern Language Association (MLA)
Leng, Longlong…[et al.]. Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows. Mathematical Problems in Engineering No. 2018 (2018), pp.1-21.
https://search.emarefa.net/detail/BIM-1209514
American Medical Association (AMA)
Leng, Longlong& Zhao, Yanwei& Wang, Zheng& Wang, Hongwei& Zhang, Jingling. Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1209514
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209514