Green Vehicle Routing Optimization Based on Carbon Emission and Multiobjective Hybrid Quantum Immune Algorithm

Liu, Xiaohong; Shan, Miyuan; Zhang, Ren-Long; Zhang, Lihong

doi:10.1155/2018/8961505

Cited by 18 publications

(16 citation statements)

References 24 publications

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“…The contribution of selected works reflects in provided models, frameworks, or optimization methods. They all provide models or frameworks either by using regression modelling by Baraković and Skorin-Kapov [27][28][29], formula-based estimation methods by Tsholkas et al [30], data collection by Korhonen et al [31], optimization techniques by Liu et al [32], machine learning methods by Balachandran et al [33], etc. The research environment in all considered studies is real and all age groups were addressed (i.e., young, adults, elderly), while applications that were used are mostly web browsing and multimedia IoT applications.…”

Section: Impact Of Qoe On Qolmentioning

confidence: 99%

Quality of Life, Quality of Experience, and Security Perception in Web of Things: An Overview of Research Opportunities

et al. 2020

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The Web of Things (WoT) is a technology concept that allows the integration of the Internet of Things (IoT) with the World Wide Web (WWW). It will vastly affect our lives in the near future given that it offers new services and applications via the well-known web window. In todays’ world where one can hardly imagine everyday life without access to various online services and applications via a plethora of devices, one can notice that technology has a huge impact on our day-to-day quality of living. That is why a user’s Quality of Experience (QoE) towards used technology in general plays a crucial role in their Quality of Life (QoL). Furthermore, security perception in terms of technology is the feature that vastly affects QoE and, consequently, QoL, as the number of security and privacy threats, risks, and vulnerabilities in cyber space, i.e., the technology environment that we increasingly use, is constantly rising. In order to reach the ultimate goals—the adoption of WoT technology and improvement of our QoL—we must know how this important aspect of security is so far addressed and analyzed. Therefore, this paper gives a comprehensive and structured analysis of the existing literature in this field through a proposed framework and provides an overview of research opportunities that should be addressed and elaborated in future investigations.

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Section: Impact Of Qoe On Qolmentioning

confidence: 99%

Quality of Life, Quality of Experience, and Security Perception in Web of Things: An Overview of Research Opportunities

et al. 2020

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“…Among the various versions of the LRP in the literature, the LRP considering environmental effect (LCLRP) has gained many researchers' attention because environmental effects have a strong relationship to economic and social sustainability and even to public health. Similarly, the LCLRP is a more complicated NP-hard problem comprising of the LAP and the VRP with environmental effects, referred to as the pollution-routing problem (PRP) [8], green vehicle-routing problem (GVRP) [9], or eco-routing problem (ERP) [10].…”

Section: Fuel Consumption and Carbon Emission Reviewmentioning

confidence: 99%

A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints

et al. 2019

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With the aim of reducing cost, carbon emissions, and service periods and improving clients’ satisfaction with the logistics network, this paper investigates the optimization of a variant of the location-routing problem (LRP), namely the regional low-carbon LRP (RLCLRP), considering simultaneous pickup and delivery, hard time windows, and a heterogeneous fleet. In order to solve this problem, we construct a biobjective model for the RLCLRP with minimum total cost consisting of depot, vehicle rental, fuel consumption, carbon emission costs, and vehicle waiting time. This paper further proposes a novel hyper-heuristic (HH) method to tackle the biobjective model. The presented method applies a quantum-based approach as a high-level selection strategy and the great deluge, late acceptance, and environmental selection as the acceptance criteria. We examine the superior efficiency of the proposed approach and model by conducting numerical experiments using different instances. Additionally, several managerial insights are provided for logistics enterprises to plan and design a distribution network by extensively analyzing the effects of various domain parameters such as depot cost and location, client distribution, and fleet composition on key performance indicators including fuel consumption, carbon emissions, logistics costs, and travel distance and time.

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“…LRP deals with the combination of two types NP-hard decisions that often emerge in logistics: the location-allocation problem (LAP) and vehicle routing problem (VRP) (Ouhader and Kyal) [8] (Sun) [9]. Among the applications of LRP, LRP considering environmental effect such as carbon emission/fuel consumption, namely, LCLRP, has recently emerged as one of the most addressed, which also handles two NP-hard problems: LAP and pollution-routing problem (PRP) (Bektas and Laporte) [10] or green vehicle routing problem (GVRP) (Liu et al) [11].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Few key factors are concerned as simple fuel consumption, such as vehicle load, travel distance, etc. Typical cases are fuel consumption rate model (Xiao et al) [14], FCR with speed (Liu et al) [11], fuel consumption calculation (FCC) (Poonthalir and Nadarajan, Kuo et al) [3,15], and models proposed by Li et al [16].…”

Section: Literature Reviewmentioning

confidence: 99%

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Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows

Leng

Zhao

Wang

et al. 2018

Mathematical Problems in Engineering

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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.

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Green Vehicle Routing Optimization Based on Carbon Emission and Multiobjective Hybrid Quantum Immune Algorithm

Cited by 18 publications

References 24 publications

Quality of Life, Quality of Experience, and Security Perception in Web of Things: An Overview of Research Opportunities

Quality of Life, Quality of Experience, and Security Perception in Web of Things: An Overview of Research Opportunities

A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints

Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows

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