Evidence map›Paper›PMID 38921210›Full record

ArticleBiomimetics (Basel, Switzerland)2024

A Grey Wolf Optimizer Algorithm for Multi-Objective Cumulative Capacitated Vehicle Routing Problem Considering Operation Time.

Gewen Huang, Yuanhang Qi, Yanguang Cai, Yuhui Luo, Helie Huang

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gewen HuangInformation and Network Center, Jiaying University, Meizhou 514015, China.ORCID 0000-0002-6011-5091
Yuanhang QiSchool of Computer Science, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China.
Yanguang CaiSchool of Automation, Guangdong University of Technology, Guangzhou 510006, China.ORCID 0000-0002-7327-5182
Yuhui LuoSchool of Automation, Guangdong University of Technology, Guangzhou 510006, China.
Helie HuangGuangdong Science and Technology Infrastructure Centre, Guangzhou 510033, China.

Funding

fundamental research Plan and application foundation Research Project of Guangzhou City 202201011707Guangdong Basic and Applied Basic Research Foundation 2022A1515240058Key Project in Higher Education of Guangdong Province 2022ZDZX4049Key Project in Higher Education of Guangdong Province, China 2022ZDZX1045Key Project in Higher Education of Guangdong Province, China 2023ZDZX1040Science and Technology Foundation of Guangdong Province 2021A0101180005Social Public Welfare and Basic Research Project of Zhongshan City 2021B2063
6 · The paper itself

Abstract

In humanitarian aid scenarios, the model of cumulative capacitated vehicle routing problem can be used in vehicle scheduling, aiming at delivering materials to recipients as quickly as possible, thus minimizing their wait time. Traditional approaches focus on this metric, but practical implementations must also consider factors such as driver labor intensity and the capacity for on-site decision-making. To evaluate driver workload, the operation times of relief vehicles are typically used, and multi-objective modeling is employed to facilitate on-site decision-making. This paper introduces a multi-objective cumulative capacitated vehicle routing problem considering operation time (MO-CCVRP-OT). Our model is bi-objective, aiming to minimize both the cumulative wait time of disaster-affected areas and the extra expenditures incurred by the excess operation time of rescue vehicles. Based on the traditional grey wolf optimizer algorithm, this paper proposes a dynamic grey wolf optimizer algorithm with floating 2-opt (DGWO-F2OPT), which combines real number encoding with an equal-division random key and ROV rules for decoding; in addition, a dynamic non-dominated solution set update strategy is introduced. To solve MO-CCVRP-OT efficiently and increase the algorithm's convergence speed, a multi-objective improved floating 2-opt (F2OPT) local search strategy is proposed. The utopia optimum solution of DGWO-F2OPT has an average value of two fitness values that is 6.22% lower than that of DGWO-2OPT. DGWO-F2OPT's average fitness value in the algorithm comparison trials is 16.49% less than that of NS-2OPT. In the model comparison studies, MO-CCVRP-OT is 18.72% closer to the utopian point in Euclidean distance than CVRP-OT.

Indexed as

cumulative capacitated vehicle routing problemdynamic grey wolf optimizer algorithmemergency logisticsfloating 2-optmulti-objective

Identifiers

PMID38921210
PMCPMC11202152

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.